This document summarizes the rationalization of India's surface water quality monitoring program under the Hydrology Project. It discusses that while different agencies have historically monitored water quality, their objectives and methods were inconsistent. The Hydrology Project aims to design a unified monitoring network and methodology. Key points include:
- Monitoring objectives of establishing baseline quality, observing trends, and calculating pollutant fluxes.
- Stations will initially be classified as baseline, trend, or flux stations based on 3 years of data.
- Samples will be collected every 2 months at minimum to represent all seasons. Monitoring frequency may increase at some stations.
- Recommended parameters include general, nutrient, organic, and microbiological parameters depending on the station type.
This document outlines the need for establishing operation and maintenance procedures for groundwater monitoring networks in India. It discusses how piezometers and observation wells can decline in performance over time if not properly maintained. Factors like siltation, drying up, damage, and influence from nearby pumping can affect data reliability. The document emphasizes that preventative maintenance is crucial to ensure monitoring structures continue generating accurate data to inform groundwater management policies. A well-defined maintenance program is needed to systematically inspect equipment and address any issues identified.
Carolina Sanchez is a staff engineer at Wildermuth Environmental, Inc. with two years of experience in water resources engineering. Her skills include groundwater monitoring, numerical analysis, water resources, and GIS. At WEI, her tasks involve analyzing groundwater and surface water data, developing charts and maps to characterize flow systems, conducting hydrologic modeling, and preliminary design of water management facilities. She has a Master's degree in environmental fluid mechanics and hydrology from Stanford and is a licensed Professional Civil Engineer in California.
This document summarizes a study that assessed water quality in the Euphrates River in Iraq from 2007-2013 using a water quality index (WQI). Fourteen physicochemical parameters were monitored monthly at four stations along the river. The WQI was calculated to evaluate water quality at each station. Results showed mean WQI values were generally below 68, indicating "good" quality except in 2012 when quality was "excellent". The highest quality was in winter months, while lowest was in summer. Overall, the study used WQI to analyze spatial and temporal changes in Euphrates River water quality for drinking purposes over a seven year period.
1) NRCS has been using and supporting the Agricultural Conservation Planning Framework (ACPF) tool since 2015 through various pilot projects, grants, and partnerships.
2) ACPF has been tested in several CEAP watersheds across different landscapes to evaluate its effectiveness and develop it for new practices.
3) NRCS's Central National Technology Support Center (CNTSC) currently supports states interested in using ACPF through training, technical assistance, and pilot projects.
4) A new agreement between NRCS, ARS, and university partners aims to further determine NRCS's readiness for nationwide ACPF use and support its implementation in MRBI and NWQI watersheds through additional pilot testing, training
This document discusses key criteria from the Clean Water Act that affect stormwater management compliance at the site level. It explains how sections 404, 402, and 401 of the CWA, which regulate discharges to waters and wetlands, pollution discharge permits, and water quality certifications, can influence stormwater management practices beyond current state requirements. Specifically, it focuses on how Maryland's anti-degradation policy is administered through a three-tier system to provide additional protections for high quality waters known as Tier II waters. Compliance for projects affecting Tier II waters may require enhanced stormwater and erosion control best management practices.
This document provides job descriptions for various roles within a Hydrological Information System (HIS) for surface water, meteorology, groundwater, water quality, and information technology functions. It describes the key responsibilities, required qualifications and experience, and typical tasks for positions ranging from field helpers to state-level managers. Standard coding is used to identify the different functions, such as S1 to S12 for surface water jobs and G1 to G12 for groundwater roles.
In December 2014 WRT held a Catchment Based Approach and Catchment Restoration Fund Conference in Exeter. WRT's Angela Bartlett gave a a presentation of her work undertaking detailed catchment risk assessments for water quality.
The webinar covered recent regulatory developments in construction and post-construction stormwater management. It discussed changes to the EPA's Construction General Permit including new buffer requirements and timelines for stabilization. It also summarized EPA's proposed rulemaking to strengthen post-construction stormwater requirements and establish national performance standards for new development. Finally, it reviewed federal requirements for stormwater management on federal facilities.
This document outlines the need for establishing operation and maintenance procedures for groundwater monitoring networks in India. It discusses how piezometers and observation wells can decline in performance over time if not properly maintained. Factors like siltation, drying up, damage, and influence from nearby pumping can affect data reliability. The document emphasizes that preventative maintenance is crucial to ensure monitoring structures continue generating accurate data to inform groundwater management policies. A well-defined maintenance program is needed to systematically inspect equipment and address any issues identified.
Carolina Sanchez is a staff engineer at Wildermuth Environmental, Inc. with two years of experience in water resources engineering. Her skills include groundwater monitoring, numerical analysis, water resources, and GIS. At WEI, her tasks involve analyzing groundwater and surface water data, developing charts and maps to characterize flow systems, conducting hydrologic modeling, and preliminary design of water management facilities. She has a Master's degree in environmental fluid mechanics and hydrology from Stanford and is a licensed Professional Civil Engineer in California.
This document summarizes a study that assessed water quality in the Euphrates River in Iraq from 2007-2013 using a water quality index (WQI). Fourteen physicochemical parameters were monitored monthly at four stations along the river. The WQI was calculated to evaluate water quality at each station. Results showed mean WQI values were generally below 68, indicating "good" quality except in 2012 when quality was "excellent". The highest quality was in winter months, while lowest was in summer. Overall, the study used WQI to analyze spatial and temporal changes in Euphrates River water quality for drinking purposes over a seven year period.
1) NRCS has been using and supporting the Agricultural Conservation Planning Framework (ACPF) tool since 2015 through various pilot projects, grants, and partnerships.
2) ACPF has been tested in several CEAP watersheds across different landscapes to evaluate its effectiveness and develop it for new practices.
3) NRCS's Central National Technology Support Center (CNTSC) currently supports states interested in using ACPF through training, technical assistance, and pilot projects.
4) A new agreement between NRCS, ARS, and university partners aims to further determine NRCS's readiness for nationwide ACPF use and support its implementation in MRBI and NWQI watersheds through additional pilot testing, training
This document discusses key criteria from the Clean Water Act that affect stormwater management compliance at the site level. It explains how sections 404, 402, and 401 of the CWA, which regulate discharges to waters and wetlands, pollution discharge permits, and water quality certifications, can influence stormwater management practices beyond current state requirements. Specifically, it focuses on how Maryland's anti-degradation policy is administered through a three-tier system to provide additional protections for high quality waters known as Tier II waters. Compliance for projects affecting Tier II waters may require enhanced stormwater and erosion control best management practices.
This document provides job descriptions for various roles within a Hydrological Information System (HIS) for surface water, meteorology, groundwater, water quality, and information technology functions. It describes the key responsibilities, required qualifications and experience, and typical tasks for positions ranging from field helpers to state-level managers. Standard coding is used to identify the different functions, such as S1 to S12 for surface water jobs and G1 to G12 for groundwater roles.
In December 2014 WRT held a Catchment Based Approach and Catchment Restoration Fund Conference in Exeter. WRT's Angela Bartlett gave a a presentation of her work undertaking detailed catchment risk assessments for water quality.
The webinar covered recent regulatory developments in construction and post-construction stormwater management. It discussed changes to the EPA's Construction General Permit including new buffer requirements and timelines for stabilization. It also summarized EPA's proposed rulemaking to strengthen post-construction stormwater requirements and establish national performance standards for new development. Finally, it reviewed federal requirements for stormwater management on federal facilities.
This document provides guidance on designing and conducting aquifer pumping tests to determine the hydraulic properties of aquifers. It outlines the necessary planning steps, including developing a conceptual model of the aquifer using all available data on geology, hydrology, and existing wells. Properly designed tests that control discharge and monitor observation wells can provide accurate estimates of aquifer transmissivity, storativity, boundaries, and other properties needed to characterize groundwater flow. Conducting short pump tests or slug tests alone does not provide all the necessary information.
The document provides guidance on conducting pumping tests for water wells. It discusses the importance of pumping tests for determining a well's sustainable yield and performance. The document outlines the basic preparations needed for pumping tests, including gathering information on the well and acquiring basic monitoring equipment to measure water levels and pumping rates. It describes the main types of pumping tests as step tests, constant-rate tests, and recovery tests. The document is intended as a practical guide for water and habitat engineers working in remote areas to help evaluate wells and aquifers under field conditions.
This document summarizes a study that evaluated the quality of drainage water in Al-Shamiya al-sharqi drain in Diwaniya city, Iraq for use in irrigation. 10 water samples were collected from locations along the drain and analyzed for various chemical parameters. An Irrigation Water Quality Index (IWQI) was used to assess the water quality, taking into account parameters like EC, sodium, chloride, bicarbonate and SAR that most affect water quality for irrigation. The IWQI was then integrated with a GIS system to map the water quality. The results found that 52% of the drainage water fell in the "Low restriction" category, 47% was "Moderate restriction" and 1% was
This document discusses catchment management and abstractions. It provides learning objectives on abstraction risk, impacts from abstractions, environmental flows, and potential measures. It then discusses various topics related to abstractions including risk assessment, impacts from abstractions, environmental flows, and existing and future measures for regulating abstractions. Drinking water safety plans, groundwater protection plans, and integrated catchment management are also summarized as they relate to abstraction and drinking water quality.
The USGS is a science agency within the Department of Interior that conducts research on water resources, ecosystems, energy and minerals. The Texas Water Science Center conducts studies in cooperation with GCDs to understand groundwater resources. Existing cooperative studies involve data collection and analysis, conceptual modeling, and groundwater modeling. Potential areas of future cooperation include studying brackish water, surface water interactions with groundwater, and additional modeling.
DSD-INT 2015 - The future of computer modeling of coastal wetland, estuarine,...Deltares
The document summarizes a modeling project to simulate coastal wetland, estuarine, and riverine systems in Louisiana. It involved a team effort between multiple organizations. The goal was to develop a validated model to simulate morphological processes during new delta and wetland creation, as well as nutrient effects on vegetation and primary producers. The modeling approach coupled hydrodynamic, morphodynamic, and nutrient dynamic modules. Nine production runs were planned using different scenarios of sediment diversion operations and environmental conditions over 50 years. Model calibration and validation showed good performance in simulating river hydrology and morphology change. The scenarios suggested that operating multiple sediment diversions could significantly build land compared to no diversions.
This document provides guidelines for conducting water sector governance assessments in Africa to improve the sustainability of water projects. It outlines six stages of the project cycle and the appropriate assessment tool to use at each stage. These include a light assessment for initial overview, rapid assessment to identify risk areas, and a more comprehensive project preparation assessment. The project preparation assessment informs the project appraisal report, indicators for project supervision, and outcomes for project completion. Scoring guidelines are provided to identify priority areas of governance concern requiring attention in a project. The assessments are designed to characterize governance and mitigate risks at all stages of the project cycle from identification to completion.
Scheme for the construction of water channelsmirzaqadeer
we are giving only idea for making water channel for poor less un economical area for different counties where people need water for drinking we present presentation in univsty CIIT
Analysis of groundwater quality of visnagar taluka, mehasana district gujaratvishvam Pancholi
Ground water is the principal source of drinking water in our country and indispensable source of our life. The quality of water is of vital concern for mankind, since it is directly linked to human welfare. The present work investigated various physiochemical parameters of villages of Visnagar taluka of Mehsana district, Gujarat. Because of north Gujarat is affected by various water quality parameters like fluoride is high in many parts of north Gujarat. A total of 50 water samples will be collected from the tube wells for post-monsoon season and analyzed for the various physiochemical parameters like pH, electrical conductivity (EC), nitrate (NO3-), magnesium (Mg2+), Calcium (Ca2+), hardness, and alkalinity, sulphates (SO42-), chloride (Cl-), sodium (Na+), potassium (K+), Fluoride (F-) and total dissolved solids (TDS). The result were compared with standards prescribed by IS: 10500(2012). It was found that the ground water contaminated at 16 sampling sites namely Khadalpur, Chhogala, Sunshi, Denap, Jetalvasana, Tarabh, Visnagar Rural, Bhalak, Kamalpur (GOT), Kamalpur (KHA), Kansa, Magaroda, Pudgam, Sadutala, Thalota, Vadu while other 34 sampling sites showed physiochemical parameters within the water quality standards and quality of water is good so it is fit for drinking uses.
master thesis the application of environmetric technique in the water qualit...Eina Fazlina Mohd Saleh
This document is the thesis submitted by Mohamad Romizan Bin Osman for the Master of Science degree at Universiti Sultan Zainal Abidin in 2018. The thesis examines the application of environmetric techniques to assess water quality in the Kuantan River in Malaysia. Water quality parameters were measured at 12 stations along the river, including biological oxygen demand, chemical oxygen demand, dissolved oxygen, pH, turbidity, salinity, and various heavy metals. Principal component analysis, cluster analysis, and discriminant analysis were used to classify water quality, identify significant parameters, and determine pollution sources. The analyses found four clusters of water quality and identified 14 key parameters. Heavy metal levels above guidelines were linked to surrounding mining and agricultural activities
Nutrient Criteria for Streams and RiversEPA Framework for Nutrient Reduction
Texas Water Conservation Association
Water Quality Subcommittee
October 13, 2011
Jim Davenport
WQ Monitoring & Assessment Section
WQ Planning Division Office of Water, TCEQ
Monitoring water supplies and sanitation in EthiopiaIRC
The document summarizes Ethiopia's National WASH Inventory, which aims to establish a reliable sector-wide monitoring and evaluation system for water, sanitation, and hygiene (WASH) access and services. Some key points:
- The inventory collected data on rural and urban water supply schemes, household water and sanitation access, and WASH in schools and health facilities.
- Preliminary analysis found over 90,000 rural water schemes and data was collected from over 12 million households.
- The inventory intends to provide baseline data for planning, strengthen monitoring, and integrate WASH actors by collecting data at all administrative levels.
- Issues in data collection included missing GPS coordinates, lack of training,
Pierce County (WA) Surface Water Management's 2011 Workplan - NisquallyNisqually River Council
The Water Quality and Watersheds Section of Pierce County SWM has outlined their 2011 workplan to improve ecosystem health through stormwater management, watershed monitoring, and partnerships. Their objectives include expanding inspections and technical assistance, issuing an updated watershed health report card including new lakes, completing a flood hazard plan, continuing water quality and salmon monitoring programs, and satisfying agreements related to the county's NPDES stormwater permit. The section will also enhance data analysis and management efforts and provide ongoing support for watershed councils and other partners.
Discharge and Sediment Transport Modeling Buck Creek ProposalJames Blumenschein
This document proposes modeling discharge and sediment transport in Buck Creek before modifications to a recreational structure. The purpose is to create a stage-discharge rating curve upstream of the structure. Field data on discharge and cross-sectional surveys will be collected using GPS and acoustic Doppler equipment. The HEC-RAS model will be used to extend the existing post-modification rating curve to higher discharges using a step-backwater method. The objectives are to establish elevations, collect survey and field data, create a stage-discharge curve, and better understand changes from the modified structure.
7 - AECOM Water Resources Seminar World Bank -16-Septindiawrm
The document discusses AECOM's work on rehabilitating the Pattamundai Canal System in Odisha, India. It overviews AECOM's scope of work, which included surveys, design, drawings and cost estimates. It describes the canal system and key challenges including lack of data on the old system. AECOM's methodology involved condition surveys, GIS mapping, designs for canal modifications and new structures, and contract documents. The process included surveys, investigation, planning, design, quantities and cost estimation, and completion documents.
This document provides information about a training module on understanding stage-discharge relations being conducted by the Central Water Commission of India. The training is aimed at middle level engineers and will cover topics like correlation and regression analysis, classification of controls, characteristics of rating curves, extrapolation of rating curves, and shifts in discharge ratings. The module will be 90 minutes long and use methods like lectures, discussions and questioning. The objectives are to help officers understand stage-discharge relations and impart this training to supervisors and junior staff.
The document analyzes water quality parameters of the Al-Kufa River in Iraq using geographical information systems (GIS). Water samples were collected from seven sites along the river from July 2013 to June 2014 and tested for 13 parameters. GIS was used to map the spatial distribution of pollutants. Analysis found that most parameters exceeded Iraqi drinking water standards but met standards for irrigation, though total hardness was higher than allowed. Sodium levels posed no risk to plants. Water quality made it unacceptable for some industries. GIS mapping showed pollution levels along the river.
This document summarizes concerns with draft Watershed Management Programs (WMPs) from a non-governmental organization perspective. Key concerns include WMPs relying on non-site specific data, insufficient prioritization of pollutants, unreasonable timelines that extend past permit deadlines, and monitoring plans not able to identify responsible parties for water quality issues. The document calls for WMPs to more specifically classify pollutants, justify strategies to reduce pollution, and not overrely on future changes or adaptive management to meet permit requirements.
Abstract— 11 wells in Wadi Fatimah were chosen to perform this study. The studied area was classified into three regions namely Abo-Hassani, Al-Khief, and Allaf. In Abo-Hassani, the water quality agrees with the WHO standards. The TDS was between 175 and 339 ppm. The hardness was below 193 ppm. The sodium and the chloride were below 71 and 63 ppm, respectively. The water here suffers from the presence of E.Coli. In Al-Kheif region, the water suffers from the high TDS 1077 ppm and the presence of E. Coli. In Allaf region the TDS was high a little (487 ppm), but still within WHO standards for drinking water. In this region, the sulfate value and the total hardness were above 250 ppm, which exceeds the WHO standards.
The document presents a Canada-wide Framework for Water Quality Monitoring. It provides guidance for jurisdictions to develop consistent and coordinated water quality monitoring programs across Canada. The Framework recommends a nationally consistent approach to establishing monitoring objectives, program design, site selection, data management, interpretation and reporting. It also calls for greater coordination among jurisdictions to develop tools to support a network of monitoring sites of national, regional and local interest.
Academia session: Joan Rose, Michigan State University , 16th January UN Wate...water-decade
This document discusses using risk assessment as a tool to improve water quality and the role of higher education institutions. It provides an overview of a conference on this topic, including discussion questions on various issues like how water quality is impacting health globally, how to integrate science and policy in risk analysis frameworks, and the future of water education curricula. The document also discusses challenges like population growth pressures on water resources and fecal contamination of water supplies. It advocates using risk assessment and other tools within a multi-disciplinary approach to address these challenges and protect water quality and public health.
The document summarizes the report of an expert group on water quality monitoring systems in India. Key points include:
- Various agencies monitor water quality but lack coordination, resulting in inconsistent data that is difficult to analyze.
- The expert group was formed to review current monitoring programs and develop a unified protocol.
- The group reviewed objectives, network design, sampling procedures, quality assurance, data management, and made recommendations including the need for referral labs and a training institute.
- The goal is to standardize monitoring so data can be shared and used to better protect national water resources from pollution.
This document provides guidance on designing and conducting aquifer pumping tests to determine the hydraulic properties of aquifers. It outlines the necessary planning steps, including developing a conceptual model of the aquifer using all available data on geology, hydrology, and existing wells. Properly designed tests that control discharge and monitor observation wells can provide accurate estimates of aquifer transmissivity, storativity, boundaries, and other properties needed to characterize groundwater flow. Conducting short pump tests or slug tests alone does not provide all the necessary information.
The document provides guidance on conducting pumping tests for water wells. It discusses the importance of pumping tests for determining a well's sustainable yield and performance. The document outlines the basic preparations needed for pumping tests, including gathering information on the well and acquiring basic monitoring equipment to measure water levels and pumping rates. It describes the main types of pumping tests as step tests, constant-rate tests, and recovery tests. The document is intended as a practical guide for water and habitat engineers working in remote areas to help evaluate wells and aquifers under field conditions.
This document summarizes a study that evaluated the quality of drainage water in Al-Shamiya al-sharqi drain in Diwaniya city, Iraq for use in irrigation. 10 water samples were collected from locations along the drain and analyzed for various chemical parameters. An Irrigation Water Quality Index (IWQI) was used to assess the water quality, taking into account parameters like EC, sodium, chloride, bicarbonate and SAR that most affect water quality for irrigation. The IWQI was then integrated with a GIS system to map the water quality. The results found that 52% of the drainage water fell in the "Low restriction" category, 47% was "Moderate restriction" and 1% was
This document discusses catchment management and abstractions. It provides learning objectives on abstraction risk, impacts from abstractions, environmental flows, and potential measures. It then discusses various topics related to abstractions including risk assessment, impacts from abstractions, environmental flows, and existing and future measures for regulating abstractions. Drinking water safety plans, groundwater protection plans, and integrated catchment management are also summarized as they relate to abstraction and drinking water quality.
The USGS is a science agency within the Department of Interior that conducts research on water resources, ecosystems, energy and minerals. The Texas Water Science Center conducts studies in cooperation with GCDs to understand groundwater resources. Existing cooperative studies involve data collection and analysis, conceptual modeling, and groundwater modeling. Potential areas of future cooperation include studying brackish water, surface water interactions with groundwater, and additional modeling.
DSD-INT 2015 - The future of computer modeling of coastal wetland, estuarine,...Deltares
The document summarizes a modeling project to simulate coastal wetland, estuarine, and riverine systems in Louisiana. It involved a team effort between multiple organizations. The goal was to develop a validated model to simulate morphological processes during new delta and wetland creation, as well as nutrient effects on vegetation and primary producers. The modeling approach coupled hydrodynamic, morphodynamic, and nutrient dynamic modules. Nine production runs were planned using different scenarios of sediment diversion operations and environmental conditions over 50 years. Model calibration and validation showed good performance in simulating river hydrology and morphology change. The scenarios suggested that operating multiple sediment diversions could significantly build land compared to no diversions.
This document provides guidelines for conducting water sector governance assessments in Africa to improve the sustainability of water projects. It outlines six stages of the project cycle and the appropriate assessment tool to use at each stage. These include a light assessment for initial overview, rapid assessment to identify risk areas, and a more comprehensive project preparation assessment. The project preparation assessment informs the project appraisal report, indicators for project supervision, and outcomes for project completion. Scoring guidelines are provided to identify priority areas of governance concern requiring attention in a project. The assessments are designed to characterize governance and mitigate risks at all stages of the project cycle from identification to completion.
Scheme for the construction of water channelsmirzaqadeer
we are giving only idea for making water channel for poor less un economical area for different counties where people need water for drinking we present presentation in univsty CIIT
Analysis of groundwater quality of visnagar taluka, mehasana district gujaratvishvam Pancholi
Ground water is the principal source of drinking water in our country and indispensable source of our life. The quality of water is of vital concern for mankind, since it is directly linked to human welfare. The present work investigated various physiochemical parameters of villages of Visnagar taluka of Mehsana district, Gujarat. Because of north Gujarat is affected by various water quality parameters like fluoride is high in many parts of north Gujarat. A total of 50 water samples will be collected from the tube wells for post-monsoon season and analyzed for the various physiochemical parameters like pH, electrical conductivity (EC), nitrate (NO3-), magnesium (Mg2+), Calcium (Ca2+), hardness, and alkalinity, sulphates (SO42-), chloride (Cl-), sodium (Na+), potassium (K+), Fluoride (F-) and total dissolved solids (TDS). The result were compared with standards prescribed by IS: 10500(2012). It was found that the ground water contaminated at 16 sampling sites namely Khadalpur, Chhogala, Sunshi, Denap, Jetalvasana, Tarabh, Visnagar Rural, Bhalak, Kamalpur (GOT), Kamalpur (KHA), Kansa, Magaroda, Pudgam, Sadutala, Thalota, Vadu while other 34 sampling sites showed physiochemical parameters within the water quality standards and quality of water is good so it is fit for drinking uses.
master thesis the application of environmetric technique in the water qualit...Eina Fazlina Mohd Saleh
This document is the thesis submitted by Mohamad Romizan Bin Osman for the Master of Science degree at Universiti Sultan Zainal Abidin in 2018. The thesis examines the application of environmetric techniques to assess water quality in the Kuantan River in Malaysia. Water quality parameters were measured at 12 stations along the river, including biological oxygen demand, chemical oxygen demand, dissolved oxygen, pH, turbidity, salinity, and various heavy metals. Principal component analysis, cluster analysis, and discriminant analysis were used to classify water quality, identify significant parameters, and determine pollution sources. The analyses found four clusters of water quality and identified 14 key parameters. Heavy metal levels above guidelines were linked to surrounding mining and agricultural activities
Nutrient Criteria for Streams and RiversEPA Framework for Nutrient Reduction
Texas Water Conservation Association
Water Quality Subcommittee
October 13, 2011
Jim Davenport
WQ Monitoring & Assessment Section
WQ Planning Division Office of Water, TCEQ
Monitoring water supplies and sanitation in EthiopiaIRC
The document summarizes Ethiopia's National WASH Inventory, which aims to establish a reliable sector-wide monitoring and evaluation system for water, sanitation, and hygiene (WASH) access and services. Some key points:
- The inventory collected data on rural and urban water supply schemes, household water and sanitation access, and WASH in schools and health facilities.
- Preliminary analysis found over 90,000 rural water schemes and data was collected from over 12 million households.
- The inventory intends to provide baseline data for planning, strengthen monitoring, and integrate WASH actors by collecting data at all administrative levels.
- Issues in data collection included missing GPS coordinates, lack of training,
Pierce County (WA) Surface Water Management's 2011 Workplan - NisquallyNisqually River Council
The Water Quality and Watersheds Section of Pierce County SWM has outlined their 2011 workplan to improve ecosystem health through stormwater management, watershed monitoring, and partnerships. Their objectives include expanding inspections and technical assistance, issuing an updated watershed health report card including new lakes, completing a flood hazard plan, continuing water quality and salmon monitoring programs, and satisfying agreements related to the county's NPDES stormwater permit. The section will also enhance data analysis and management efforts and provide ongoing support for watershed councils and other partners.
Discharge and Sediment Transport Modeling Buck Creek ProposalJames Blumenschein
This document proposes modeling discharge and sediment transport in Buck Creek before modifications to a recreational structure. The purpose is to create a stage-discharge rating curve upstream of the structure. Field data on discharge and cross-sectional surveys will be collected using GPS and acoustic Doppler equipment. The HEC-RAS model will be used to extend the existing post-modification rating curve to higher discharges using a step-backwater method. The objectives are to establish elevations, collect survey and field data, create a stage-discharge curve, and better understand changes from the modified structure.
7 - AECOM Water Resources Seminar World Bank -16-Septindiawrm
The document discusses AECOM's work on rehabilitating the Pattamundai Canal System in Odisha, India. It overviews AECOM's scope of work, which included surveys, design, drawings and cost estimates. It describes the canal system and key challenges including lack of data on the old system. AECOM's methodology involved condition surveys, GIS mapping, designs for canal modifications and new structures, and contract documents. The process included surveys, investigation, planning, design, quantities and cost estimation, and completion documents.
This document provides information about a training module on understanding stage-discharge relations being conducted by the Central Water Commission of India. The training is aimed at middle level engineers and will cover topics like correlation and regression analysis, classification of controls, characteristics of rating curves, extrapolation of rating curves, and shifts in discharge ratings. The module will be 90 minutes long and use methods like lectures, discussions and questioning. The objectives are to help officers understand stage-discharge relations and impart this training to supervisors and junior staff.
The document analyzes water quality parameters of the Al-Kufa River in Iraq using geographical information systems (GIS). Water samples were collected from seven sites along the river from July 2013 to June 2014 and tested for 13 parameters. GIS was used to map the spatial distribution of pollutants. Analysis found that most parameters exceeded Iraqi drinking water standards but met standards for irrigation, though total hardness was higher than allowed. Sodium levels posed no risk to plants. Water quality made it unacceptable for some industries. GIS mapping showed pollution levels along the river.
This document summarizes concerns with draft Watershed Management Programs (WMPs) from a non-governmental organization perspective. Key concerns include WMPs relying on non-site specific data, insufficient prioritization of pollutants, unreasonable timelines that extend past permit deadlines, and monitoring plans not able to identify responsible parties for water quality issues. The document calls for WMPs to more specifically classify pollutants, justify strategies to reduce pollution, and not overrely on future changes or adaptive management to meet permit requirements.
Abstract— 11 wells in Wadi Fatimah were chosen to perform this study. The studied area was classified into three regions namely Abo-Hassani, Al-Khief, and Allaf. In Abo-Hassani, the water quality agrees with the WHO standards. The TDS was between 175 and 339 ppm. The hardness was below 193 ppm. The sodium and the chloride were below 71 and 63 ppm, respectively. The water here suffers from the presence of E.Coli. In Al-Kheif region, the water suffers from the high TDS 1077 ppm and the presence of E. Coli. In Allaf region the TDS was high a little (487 ppm), but still within WHO standards for drinking water. In this region, the sulfate value and the total hardness were above 250 ppm, which exceeds the WHO standards.
The document presents a Canada-wide Framework for Water Quality Monitoring. It provides guidance for jurisdictions to develop consistent and coordinated water quality monitoring programs across Canada. The Framework recommends a nationally consistent approach to establishing monitoring objectives, program design, site selection, data management, interpretation and reporting. It also calls for greater coordination among jurisdictions to develop tools to support a network of monitoring sites of national, regional and local interest.
Academia session: Joan Rose, Michigan State University , 16th January UN Wate...water-decade
This document discusses using risk assessment as a tool to improve water quality and the role of higher education institutions. It provides an overview of a conference on this topic, including discussion questions on various issues like how water quality is impacting health globally, how to integrate science and policy in risk analysis frameworks, and the future of water education curricula. The document also discusses challenges like population growth pressures on water resources and fecal contamination of water supplies. It advocates using risk assessment and other tools within a multi-disciplinary approach to address these challenges and protect water quality and public health.
The document summarizes the report of an expert group on water quality monitoring systems in India. Key points include:
- Various agencies monitor water quality but lack coordination, resulting in inconsistent data that is difficult to analyze.
- The expert group was formed to review current monitoring programs and develop a unified protocol.
- The group reviewed objectives, network design, sampling procedures, quality assurance, data management, and made recommendations including the need for referral labs and a training institute.
- The goal is to standardize monitoring so data can be shared and used to better protect national water resources from pollution.
This document summarizes the report of an expert group on water quality monitoring systems in India. The group was tasked with streamlining the varying water quality monitoring systems used by different agencies. The group reviewed current monitoring programs, sampling procedures, laboratory needs, and quality control. It developed a unified water quality monitoring protocol and recommended establishing central training institutes and two referral laboratories to help standardize the process and ensure reliable data across agencies. The report provides the framework to coordinate water quality monitoring efforts for effective national water resources management.
Risk assessment as a tool to improve water quality and the role of institutio...ILRI
Presentation by Kyana Young, Joan B. Rose, John Fawell, Rosina Girones Llop, Hung Nguyen-Viet and Maureen Taylor at the 2015 UN-Water Annual International Zaragoza Conference, Zaragoza, Spain,15-17 January 2015.
Handout prepared to the "Introduction to water and waste water management|.
Brief introduction about water and wastewater monitoring.
Contact: adnansirage@gmail.com
Climate Resilient Water Safety Plan ImplementationIRC
The Water Development Commission shared the experience with the Climate Resilient Water Safety Plan (CR WSP) implementation approach in Ethiopia during a learning workshop. This workshop was held in Adama, Ethiopia, on 23 September 2021.
Evaluating and Developing of Water Resources Quality Monitoring Program Imple...IJERD Editor
Evaluating effectiveness of monitoring program is important element in reviewing loop to improve
program performance and program development. In this study, the water resource monitoring program
implemented by ministry of environment have been evaluated to address strengthens and weakness points.
Program has evaluated against monitoring objectives, monitoring parameters, regulatory compliance, data
product, and institutional and human competence. Evolving monitoring program has been required to overcome
some hampered such as unclear objectives, limited parameters, Lacks in quality control procedures and quality
assurance procedures, absence of data analysis and management, and shortage of specialized expertise. The
program have many of the strengths factors that can be built on such as it have institutional structure and good
hierarchy, the human resources, a lot of equipment and laboratory facilities with good capabilities, accumulated
experience, historical data on general water quality parameters which gives an overview of the pollution sources
and water quality. It's important to develop water resources monitoring program in the light of the national
strategy of environment adopted by ministry of environment and based on principle concepts and approaches
such as integrated water resource quality management, design on catchment context, inclusion of biotic
indicator, aquatic ecological health approach, and data product to support decision making.
Drinking Water Quality Monitoring & Sur veillance F rame workBhavin Kanani
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This curriculum vitae outlines the professional experience and qualifications of Alan Kleinschmidt. It summarizes his role managing water operations for Toowoomba Regional Council, where he oversaw the functionalization of water and wastewater operations across multiple councils. It also describes his experience developing drinking water quality management plans, improving environmental compliance and recycled water management, and representing the Queensland water industry on various committees. The CV lists his education qualifications and provides contact details for a reference.
The document discusses India's efforts to provide safe drinking water to its population. It notes that in 1975, over 1 billion people globally lacked access to safe water. In response, India developed various five-year plans from 1980-1997 to expand access, with the goal of supplying safe water to all rural villages. Key aspects of ensuring water safety discussed include water quality standards, testing for contaminants, monitoring programs, and strategies like water treatment and sanitation inspections. The document also examines health impacts of contaminated water and international targets for access to improved water sources.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
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New England Water Treatment Training (NEWTT): Presentation by Robert S. Rak, Principal Investigator, Professor and Environmental Science and Technology Coordinator, Bristol Community College, Fall River, MA
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IRJET- Smart Water Monitoring System for Real-Time Water Quality and Usage Mo...IRJET Journal
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Evaluation of Potential Physico-Chemical Ground Water Pollution: a Case Study...EditorIJAERD
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quality. The pH, DO, temperature, turbidity, chlorine, iron, water hardness, potassium and calcium were analysed. All the
parameters studied were within the stipulated levels except iron, and chloride for samples from point C (Ebenezer Hostel).
Turbidity for samples from points A and C were above the permissible levels of KEBs standards. The water sampled from
point A and C may require further treatment to allow for domestic use. This analysis revealed to some extent a healthier
system, though further analysis is needed to support this assertion. Continuous monitoring of the groundwater sources
within KM should be taken on regular basis to detect any changes and to sustainably maintain the quality of water within
the required KEBs water quality standards.
ICSEIET23 Paper_Id_655.pptx paper publishRonaldoMantis
This document describes the development and implementation of a water quality monitoring system for the Ganga River. The system uses sensors to continuously monitor key water quality parameters like pH, temperature, dissolved oxygen and conductivity. The sensor data is wirelessly transmitted to a centralized database in real-time. The system enables real-time monitoring of water quality, early detection of issues, and ensures water meets WHO standards for drinking water. It was found to be effective for improved water management and environmental sustainability.
This document provides guidance on investigating and selecting sites for hydrological observation stations. It discusses the importance of establishing a network of stations to collect hydrological data and assess water resources. The key steps in designing a hydrological observation station network include:
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2. Establishing subsequent stations where significant changes in flow volume occur, like below a major tributary confluence.
3. Considering other factors like assessing water loss from channels and providing information for various planning purposes.
The collected data is crucial for water resource planning and management activities like utilization, project formulation, and dispute resolution.
This document provides an operations manual for water quality analysis laboratories. It discusses good laboratory practices and quality assurance protocols that should be followed, including procedures for sample handling, analytical methods, equipment maintenance, and data recording. Standard analytical methods are described for over 40 water quality parameters. Laboratories are expected to adhere to proper chemical and equipment handling techniques, quality control measures, and documentation practices to ensure reliable and comparable analytical results.
This document provides an overview of the Ground Water Data Entry Software (GWDES) developed for the Hydrology Project. GWDES allows for entry, validation, and visualization of time-dependent and -independent groundwater data. It features customized data entry screens, user authorization, and export/import capabilities. The document outlines the key modules, reports, and analysis features of GWDES for managing groundwater level, quality, lithology, and rainfall data for various states in India.
This document discusses groundwater usage and management in India. It notes that groundwater provides 38% of India's total usable water resources and is critical for irrigation, rural drinking water, and urban water supply. However, over 60% of assessment units have been designated as overexploited, and groundwater levels are declining in many areas. The Central Ground Water Board's new scheme aims to shift from groundwater development to management through comprehensive aquifer mapping, formulation of aquifer management plans, capacity building, and regulation. Key goals are improving data accuracy, managing aquifers at the local level through participation, and achieving water security and sustainability. Major initiatives include the National Aquifer Mapping project and participatory groundwater management programs.
Tools for water resources planning decision support system planning dss (p) nihhydrologyproject2
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The document summarizes an awareness workshop on integrated water resources management applications developed under a hydrology project. It describes the objectives of developing standardized hydrological design practices and tools. It outlines the main components of the Hydrological Design Aids software, including modules for water availability assessment, design flood estimation, and sedimentation rate estimation. It provides an overview of the software architecture and features for entering project details, station data, and performing analyses like unit hydrograph development and peak flood estimation. Regional models are being developed for four river systems to enable computation of monthly water yields for ungauged sub-basins.
The document describes an online surface water information system called eSWIS that consists of three software applications: SWDES 3.0, HYMOS, and WISDOM. It notes issues with the existing standalone desktop software applications and outlines plans to replace them with an integrated web-based system. Key features of the new eSWIS system include centralized data storage, role-based access controls, offline data entry capabilities, and decreased time from data entry to dissemination.
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Mh gw techno economic feasibility of artificial recharge of aquifer as a mit...hydrologyproject2
1. The document discusses a techno-economic feasibility study of artificial groundwater recharge as a mitigation measure for fluoride contamination in villages in Yavatmal District, Maharashtra, India.
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Hp wq study of ground water quality characteristics in industrially predomina...hydrologyproject2
This document provides an executive summary of a study conducted to assess groundwater quality characteristics in industrially predominant areas of Himachal Pradesh. The study was conducted in two phases: the first involved collecting groundwater samples from deep tube wells and analyzing water quality parameters, while the second involved additional sampling from shallow tube wells to better understand spatial and temporal variations in water quality. Analysis found that groundwater quality varied spatially and some parameters exceeded permissible limits. While direct industrial impacts were not established from deep well samples, shallow well samples provided insight and detected traces of heavy metals at some locations. The study developed GIS-based maps and models to analyze spatial trends in water quality and vulnerability. It concluded that continuous long-term monitoring is
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
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Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframePrecisely
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
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Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
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Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
1. WORKSHOP
ON
SURFACE WATER QUALITY MONITORING
UNDER
HYDROLOGY PROJECT
7-8 MARCH, 2000
TECHNICAL PAPERS
Organised By
CENTRAL POLLUTION CONTROL BOARD CENTRAL WATER COMMISSION
DELHI NEW DELHI
HYDROLOGY PROJECT
2. i
Workshop on Surface Water Quality Monitoring
under Hydrology Project
(March 7- 8, 2000)
Date Time Topic of Discussion Speakers
0930 – 1000 Registration
1000 – 1030 Inauguration
Chief Guest- Chairman, CWC;
Chairman, CPCB; Member (RM),
CWC; and Team Leader, HP
1030 – 1100 Tea
Technical Session I : Objectives, Issues & Mandates on SW-WQ Monitoring
Session Chairman : Prof. Dilip Biswas, Chairman, CPCB
1100 – 1130 Objectives and issues Shri Indra Raj, SJC(WM), PCS
1130 -- 1200 Mandates of different agencies for
water quality monitoring
Shri A. R. Bakshi, Director (WM)
1200 --1230 Design of water quality monitoring
network
Dr. R. H. Siddiqi, HP- Consultant
1230 -- 1300 Views of State Agencies on
objectives and issues *
All
1300 - 1400 Lunch
1400 – 1500 Views of State Agencies on
mandates and network *
All
1500 – 1530 Discussions and conclusions All
Day 1
1530 – 1600 Tea
3. ii
Technical Session II : Rationalisation of Monitoring Programme
Session Chairman : Dr. J. G. Grijsen, Team Leader, Hydrology Project
1600 – 1620 Rationalisation of existing water
quality monitoring programme
including sampling location,
parameters and frequency of
sampling
Dr. M. C. Dutta, RO, RDD, CWC/
Dr. S. P. Chakrabarti, HP-Consultant
1620 – 1640 Periodic review of monitoring
programme
Er. S. C. Chadha, Director, CWC
1640 – 1700 Discussions and conclusions All
Technical Session III : Data Analysis and Information Dissemination
Session Chairman : Dr. R. H. Siddiqi, Consultant, Hydrology Project
0930 – 1000 Data validation and analysis Ms M. Villars,HP-consultant
1000 – 1030 Dissemination of Information :
Design of Year Book
Dr. Roop Narain, CWC, HP
Dr. S. P. Chakrabarti, Consultant, HP
1030 – 1100 Discussions and conclusions All
1100 – 1130 Tea
Technical Session IV : Quality Assurance
Session Chairman : Er. S. K. Das, Chief Engineer (P&D), CWC
1130 – 1200 Quality assurance – analytical
quality control
Sh. A. K. Mitra, CWC
1200 – 1230 Accreditation & recognition of Lab. Dr. M. Q. Ansari, Sr. Scientist, CPCB
Dr. S. P. Chakrabarti, Consultant, HP
1230 – 1300 Discussions and conclusions All
Day 2
1300 – 1400 Lunch
4. iii
Technical Session V : Concluding Session
Session Chairman : Prof. Dilip Biswas, Chairman, CPCB
1400 – 1445 Constraints in implementation of
sustainable monitoring programme
CWC & State Agency representatives
1445 – 1530 Conclusions & recommendations CWC-RD, HP
1530 – 1600 Tea
1600 – 1700 Valedictory function Chairman, CPCB; Sh. M. K. Sharma,
Commissioner (WM) PCS; Dr. J. G.
Grijsen. HP, Sh. Das, Chief Engr.(PD),
*Executive Engineers of Central & State Agencies to present
5. 1
ISSUES AND OBJECTIVES IN SURFACE WATER QUALITY
MONITORING PROGRAMME UNDER HYDROLOGY PROJECT
Shri Indra Raj, Sr. Joint Commissioner (WM)
Central Water commission
1. Introduction
The need for water to meet our daily requirements is ever-increasing with the growth
in population and its thirst for improved standard of living. With the spate in
industrialisation in recent years to support the human need, water requirement has
further accentuated. Rain fall being limited only during monsoon period of about
three months at a stretch, the surface water availability ranges precariously poised
between flood and drought conditions. In the process, people suffer from non-
availability of ‘quality’ water either because of contamination of this scarce resource
out of human excretions and other pollutants from agricultural activities being carried
to the water front in the form of surface wash-off, or non-availability of enough water
in rivers to dilute the untreated/partially treated municipal sewage and industrial
effluent to acceptable / permissible quality level. Health of the rivers also gets upset to
support the aquatic life forms so essential for self-purification. Irrigation with polluted
river water not only could create bio-accumulation of pollutants in crop, it has also
potential for causing soil sickness and groundwater contamination.
The Indian Parliament enacted the Water (Prevention and Control of Pollution) Act,
1974 to maintain or restore wholesomeness of water bodies so that various beneficial
usages out of this scarce wealth could be sustained.
It is, therefore, imperative to have a close watch on the quality of surface waters
through frequent monitoring so that any impairment in their quality is taken
cognisance of by the appropriate body/authority for action programmes in restoration
of quality.
6. 2
2. Monitoring of Surface Water Quality
The quality of surface water is being monitored in the country since several decades
by various agencies viz. the Central Water Commission (CWC), the State Irrigation
Departments and the Central & State Pollution Control Boards. However, the
mandates and objectives of these agencies being different, there had been no unified
procedure for monitoring to provide a holistic view of the characteristics of the water
bodies. While the interest of the CWC was mostly oriented towards the development
of the surface water resources, the river gauging & discharge measurement and
determination of sediment transport & its characteristics at limited locations, the water
quality was analysed for a few physico-chemical parameters, mainly for historical
recording purposes. The State Water Resources agencies also were confined to similar
activities, but their main interest was devoted to the determination of the suitability of
the surface water resources for use in irrigation. The interest of the Pollution Control
Boards were limited to determination of the health of the river in terms of pollution
related parameters for surveillance of water quality and determination of impact due
to discharge of pollutants through different sources. Thus the monitoring programmes
of the various agencies were like mutually exclusive events with no virtual co-
ordination among them.
The water quality monitoring programme under the Hydrology Project is currently
under implementation by the Ministry of Water Resources envisages to improve upon
the existing set-up. The Project aims to strengthen the water quality monitoring
programme of the Central and State agencies with an integrated approach.
3. Issues to be Addressed
Investigation of the present incohorent and inadequate water quality monitoring
system of the various agencies revealed that the following areas need attention :
• Even if there is no specific mandate for the Central and State surface water
resources development agencies to monitor river water quality for maintaining or
7. 3
restoring wholesomeness of water bodies, it is implied that the quality of the
resources developed should be monitored to observe that it satisfies the quality
criteria to sustain the designated-best-uses. In case of non-compliance, the
information need to be passed on to the concerned agency for pollution control.
Otherwise, it would necessitate duplication of effort by such agencies which
would be expensive.
• Water quality monitoring mechanism should be uniform among all concerned
agencies for comparative results.
• Quality assurance programmes should be in-built for reliability of data.
• Analytical capability of the laboratories in terms of modern instrumental facilities
and trained manpower should be constantly upgraded at reasonable frequency.
• Monitoring programme should be reviewed at regular intervals by a State level
Committee as the riverine system is dynamic and anthropogenic activities on river
basins are fast changing due to rapid urbanisation and industrialisation.
• Water quality data generated from the monitoring programme should be validated
before storage in the Data Centre for creating the database.
• Water quality data should be transformed into information at the Data Centre for
fast dissemination among user agencies.
4. Objectives of the Hydrology Project
Keeping the above issues in view, the objectives of the Hydrology Project (HP) with
special reference to water quality monitoring programme can be summarised as
follows :
8. 4
• Designing of the monitoring network for establishing baseline water quality,
observing trend in quality changes and calculation of flux of water constituents at
representative locations, avoiding duplication among participating agencies;
• Evolving Type-designs for a three-tier system of laboratories for analysing field
parameters at level-I laboratories near to the sampling locations, physico-chemical
and bacteriological parameters including pollution related parameters in level-II
laboratories, and toxic substances including heavy metals and pesticides in level-
II+ and level-III laboratories;
• Selection of monitoring parameters and frequency for different types of stations;
• Standardisation of analytical procedures for various parameters;
• Designing specifications for state-of-the-art instruments for procurement by the
respective agencies;
• Designing methodology for ‘Analytical Quality Control’ (AQC) through ‘Within
laboratory’ and ‘Inter-laboratory’ exercises;
• Standardising procedures for data validation and data entry system; and
• Dissemination of water quality information for user agencies
5. Concluding Remarks
The Hydrology Project planned for six year duration is operational for over 4 years.
Attempts are being made on all fronts mentioned above. While considerable progress
has been made on the design aspects of the monitoring programme, some of the
activities are being delayed due to inescapable reasons in developing the
infrastructure facilities, like construction of laboratory building, procurement of some
of the analytical instruments, deployment of qualified laboratory personnel. Such
obstacles do occur when multiple organisations are involved. But sampling and
9. 5
analysis as per designed network should start with whatever resources / facilities are
available at hand which will gradually be strengthened. Water quality data should
start flowing to the Data Processing Centres for validation and for analysis, storage
and dissemination with effect from January, 2001 if not earlier. This will enable
reviewing of the monitoring mechanism for finer tuning before the Project duration
ends.
The objective of the Workshop will be best served if the participants deliberate on the
various aspects of the methodology of the monitoring programme to come to a
consensus so that uniform and consistent procedures are adopted for comparable and
reliable data generation required for water resource development and planning.
10. 6
RATIONALISATION OF SURFACE WATER QUALITY
MONITORING PROGRAMME
Dr. M. C. Dutta * and Dr. S. P. Chakrabarti **
1. Introduction
Surface water quality is being monitored since decades by several agencies of the Central
and State governments. The Central Water Commission and the State Irrigation
Departments are principally concerned with the development of surface water resources,
including measurements of river water level and discharge for flood forecasting and
flood control, and monitoring of sediment transport and its characteristics for prevention
of soil erosion in the catchment area of the basin besides analysis of physico-chemical
properties of water to ascertain its suitability for drinking and irrigation. However, there
was no specific mandate for these agencies for protection of quality of the scarce water
resources.
With the enactment of the “Water (Prevention and Control of Pollution) Act, 1974”, the
Central and State Pollution Control Boards were constituted under the provisions of this
Act with the sole objective of maintaining or restoring wholesomeness of water bodies to
meet the requirements of various beneficial uses.
In view of the differences in the objectives of the afore-mentioned agencies, their
monitoring programmes were at variance with one another. Each of these agencies has
extensive and expensive network for monitoring stations with hardly any co-ordination
among them to initiate a unified method of water sampling and analysis of surface water
for the cause of protection of its quality through quality improvement programmes.
Being concerned with the problem, the Ministry of Water Resources, Government of
India, has taken up the Hydrology Project (HP) of six year duration in collaboration with
the government of The Netherlands, to develop a national Hydrological Information
System (HIS) with user-friendly software for the benefit of the concerned agencies. The
Hydrology Project Directorate of the Central Water Commission (CWC)) has been
-----------------------------------------------------------------------------------------------------------
* Research Officer, River Data Directorate, Central Water Commission, N. Delhi-11066
**Consultant, Hydrology Project Office, 4th
Floor, CSMRS-Building, N. Delhi-110 016
11. 7
involved in the development of the methodology for designing WQ monitoring
networks, rationalisation of existing WQ monitoring programme including sampling
locations, parameters and frequency of sampling, guidelines for analytical procedures,
data validation, analytical quality control etc., which are ready for adoption by the
monitoring agencies at the Central and State levels. However, it is imperative to have
detailed deliberations on the above-mentioned issues to arrive at a consensus decision
before adoption .
2. Monitoring Objectives
The main objectives for surface water quality monitoring, as conceived under the
Hydrology Project, are as follows:
Monitoring for establishing Baseline water quality
Observing trend in water quality changes
Calculation of flux of water constituents of interest
Surveillance for ensuring quality requirements for various designated-best-uses for
their sustenance
Dissemination of data to user agencies for their water quality management
programmes
3. Frequency and Parameters
3.1 Monitoring frequency and the selection of parameters are decided keeping in view
the objectives of sampling at a particular location and the type of use the concerned
stretch of the water body is subjected to. Although the surface water agencies do have
considerable historical data stored in ‘Water Quality Year Books’, the data generated are
incomparable in view of the difference in objectives of sampling and the varying
monitoring system. Hence, it would be to consider all water quality monitoring stations
as a combination of Baseline and Trend stations to start with.
3.2 Samples shall be collected every two months viz. May / June (pre-monsoon),
August, October, December, February and April, which will fairly represent all seasons
of the year. This will generate six samples from perennial rivers and 3-4 samples from
seasonal rivers, every year.
12. 8
3.3 After data are collected for three years, the stations will have to be reclassified as
either Baseline, Trend or Flux stations after examining the data. The stations indicating
no influence of human activity on water quality will finally be classified as the Baseline
Station. Others will remain as Trend stations. If a station is classified as a Baseline
station, it will have to be monitored, after every three years, again for one year at a
frequency of every two months to observe the qualitative change, if any. If there is no
considerable change, the station will continue to be the Baseline station and it will be
monitored again after three years. Otherwise, it will have to be reclassified and
monitored as a Trend station.
3.4 If a station is classified as Trend station, it will continue to be monitored but with
an Increased frequency of once every month.
3.5 Stations will be classified as Flux stations where it is considered necessary to
measure the mass of any substance carried by the flow. The frequency of sampling at
such stations and analyses of constituents of interest may be increased to 12 or 24 times
per year. measurement of discharge at such stations is necessary.
3.6 The recommended parameters for analysis for different categories of stations are
given in Table 1.
Table 1 Parameters of analysis for surface water samplesa
Parameters Initially Baseline Trend
General Temp, EC, pH, DO, TDS Temp, EC, pH, DO,TDS Temp, EC, pH, DO
Nutrients NH3-N, NO2 + NO3, total
P
NH3-N, NO2 + NO3, total P NH3-N, NO2 + NO3, total P
Organic matter BOD, COD None BOD, COD
Major ions Ca++
, Mg++
, K+
, Na+
, CO3
-
-
, HCO3
-
, Cl-
, SO4
--
Ca++
, Mg++
, K+
, Na+
, CO3
--
,
HCO3
-
, Cl-
, SO4
--
Cl-
Other inorganics None None None
Metals None None None
Organics None None None
Microbiologicalb
Total coli. None Total and fecal coli.
Biological None None None
a- based on ‘Surface Water Quality Network Design, Guidelines and an Example’, June 1997
b- depending on workload, analysis frequency may be reduced upto 2 samples per year
13. 9
Other inorganics, metals, organics and microbiological parameters for analysis shall be
determined as a part of special survey programmes, which may include some of the
Trend stations where there is a need for determination of any of these groups of
parameters.
3.7 The survey programmes shall ordinarily be of one year duration. The sampling
frequency may be the same as that for Trend stations.
3.8 Special arrangements for sampling and transport of the samples will be necessary
for the survey programmes and microbiological samples.
4. Sample Collection
4.1 The most important aspect in the surface water quality monitoring programme is
the sampling. Location of sampling shall be so selected that the sample collected is
representative of the water quality in that stretch indicating the health of the water body.
More often than not samples are collected either from the bank or from the stagnant pool
of water near the bank or just downstream of any polluting discharge into the water
body, the quality of which is to be monitored. In all the above cases, the samples will not
be representative for obvious reasons. The samples shall invariably be collected from the
centre of the main stream of the flow/ river discharge from a depth of 30 cm from the
water surface using a weighted bottle or by means of a Dissolved Oxygen (DO) sampler
avoiding mixing of air into the water sampled. Hence, a location map of the sampling
point is essential for the sampling personnel to arrive at the exact location.
4.2 In case of surveillance stations to monitor the impact of any polluted discharge
into the water body, samples shall not be collected from immediate downstream or in
near vicinity in the same bank where the pollutants are discharged. The ideal location
will be sufficiently downstream where the pollutants discharged are thoroughly
mixed/dispersed in the medium. Such a location is to be identified through a detailed
survey.
4.3 Another extreme situation for sampling can be when the flow in the river is not
enough to dip the DO-sampler, which is very common for Indian rivers. In such
14. 10
conditions, samples shall be collected from just below the surface of the main flowing
stream avoiding floating matters and mixing of air in the sample.
4.4 In case of any deviation in the sampling point, it shall be recorded in the Sample
Identification Form to be filled for each sample, including local weather conditions at the
time of sampling.
4.5 Sample containers shall be previously cleaned before coming to site. The container
shall be rinsed with the sample at site three times before it is filled. A small air space
shall be left inside the sampling bottle to allow mixing of sample at the time of analysis.
4.6 Sample containers shall be properly identified by attaching an appropriately
inscribed tag or label. The sample code and the sampling date shall be clearly marked on
the sampler or the tag. The sample ‘Identification Form’, as shown in Figure 1, shall be
filled for each sample for each sampling occasion after doing the analysis for field
parameters. If there are more than one bottle filled at a site, it is to be registered in the
same form. Sample identification forms shall all be kept in a Master File at the level II or
II+ laboratory.
4.7 Samples from reservoir site shall be collected from the out-going canal, power
channel or water intake structure, in case water is pumped. When there is no discharge in
the canal, sample shall be collected from the upstream side of the regulator structure,
directly from the reservoir.
4.8 DO shall be determined in a sample collected in a DO bottle using a DO sampler.
The DO must be fixed immediately after collection. DO concentration can then be
determined either in the field or later, in a level I or level II laboratory.
15. 11
Figure 1 Sample identification form for surface water samples
Sample code
Observer Agency Project
Date Time Station code
Container Preservation TreatmentParameter
code Glass PVC PE Teflon None Cool Acid Other None Decant Filter
(1) Gen
(2) Bact
(3) BOD
(4) COD, NH3,NO3
-
(5) H. Metals
o T (6)Tr. Organics
Source of sample
Waterbody Point Approach Medium Matrix
o River
o Drain
o Canal
o Reservoir
o Main current
o Right bank
o Left bank
O Bridge
O Boat
O Wading
o Water
o Susp. matter
o Biota
o Sediment
o Fresh
o Brackish
o Salt
o Effluent
Sample type o Grab o Time-comp o Flow-comp o Depth-integ o Width-integ
Sample device o Weighted bottle o Pump o Depth sampler
Field determinations
Temp o
C pH EC µmho/cm DO mg/L
Odour
code
Odour free
Rotten eggs
Burnt sugar
Soapy
Fishy
) Septic
) Aromatic
) Chlorinous
) Alcoholic
(10)Unpleasant
Colour
code
Light brown
Brown
Dark brown
Light green
Green
) Dark green
) Clear
) Other (specify)
Remarks
Weather o Sunny o Cloudy o Rainy o Windy
Water vel. m/s o High (> 0.5) o Medium (0.1-0.5) o Low (< 0.1) o Standing
Water use o None o Cultivation o Bathing & washing o Cattle washing
o Melon/vegetable farming in river bed
16. 12
5. Sample Container, Preservation and Transport
5.1 The material of the container shall be such that it does not contaminate the
sample due to leaching. Preservation of samples during transportation from site to the
laboratory for analysis is also equally important. The type of container and the
preservatives to be used are indicated in Table 2.
Table 2 Types of sample containers and preservation chemicals
Analysis Type of Container Preservation
General Glass, PE None
COD, NH3, NO2
-
, NO3
-
Glass, PE H2SO4, pH<2
P Glass None
DO BOD bottle DO fixing chemicals
BOD Glass, PE 40
C, dark
Coliform Glass, PE, Sterilised 40
C, dark
Heavy metals Glass, PE HNO3, pH<2
Pesticides Glass, Teflon 40
C, dark
5.2 Samples shall be transported to concerned laboratory (level II or II+) as soon as
possible, preferably within 48 hours.
5.3 Analysis of coliforms shall be started within 24 hours of collection of sample. If
the time is exceeded, it shall be recorded with the result.
5.4 Samples containing microgramme / litre metal level, shall be stored at 40
C and
analysed as soon as possible. If the concentration is of mg/l level, it can be stored for
upto 6 months, except mercury, for which the limit is 5 weeks.
5.5 Left over samples shall be discarded only after primary validation of data.
17. 13
6. Analysis and Record
6.1 Sample receipt register
There is a need for keeping record in the laboratory as the samples arrive and are
distributed among the analysts/chemists. Each laboratory shall have a bound register,
which is to be used for registering samples as they are received. An example of the
headings and the information for such a register is given in Table 3.
Table 3 Sample receipt register
Date/Timereceived
atlab.
Date/Timecollected
Stationcode
Project
Collecting
agency/collector
Preservation
Parametercode
Lab.SampleNo.
(1) (2) (3) (4) (5) (6) (7) (8)
02.07.99/1400 01.07.99/1100 M 22 WQ monitoring SW Div II/
Singh
No 1 28-1
02.07.99/1400 01.07.99/1700 M 24 WQ monitoring SW Div II/
Singh
No 1 29-1
02.07.99/1400 01.07.99/1700 M 24 WQ monitoring SW Div II/
Singh
Yes 4 29-4
05.07.99/1100 02.07.99/1300 S 44 Survey A SPCB/
Bhat
Yes 5 30-5
The features of the above Table are as follows:
Column (3) gives the station code conventionally followed by the monitoring
agency.
Column (4) gives the project under which the sample is collected.
Column (7) corresponds to the parameter(s) code given in the sample identification
form.
18. 14
Column (8) gives the laboratory sample number assigned to the sample as it is
received in the laboratory. Note that the numbering has two parts separated by a hyphen.
The first part is assigned in a sequential manner as samples are received from various
stations. If two samples are collected at the same time from a station for different sets of
analysis, the first part of the number is the same. The second part corresponds to the
parameter code.
The results of the analyses of all the samples having the same first part of the code
would be entered in the data entry system as one sample having the same station code
and time of sample collection.
6.2 Work Assignment and Personal Registers
For accountability and comparable distribution of work among analysts/chemist, the
following procedure may be adopted:
The laboratory incharge should maintain a bound register for assignment of work.
This register would link the lab. sample number to the analyst who makes specific
analyses, such as pH, EC, BOD, etc.
An estimate of time needed for performing the analyses may also be entered in the
register.
Each laboratory analyst should have his/her own bound register, where all laboratory
readings and calculations are to be entered.
When analysis and calculations are completed, the results must be recorded in a
register containing data record sheets described in the next section.
6.3 Analysis Record and Data Validation
A recommended format for recording data is given in Figure 2. It includes all
parameters, except heavy metals and trace organics, that may be analysed in the water
quality monitoring programme currently envisaged. Ordinarily, a sample need NOT be
analysed for all the listed parameters.
19. 15
Record of analyses for heavy metals and trace organics, which will be performed
on a limited number of samples, shall be kept separately in a similar format.
Columns (2) & (3) are to be filled from the entries in the Sample Receipt Register.
Columns (4) – (9) pertain to the field measurements. This information will be available
from the Sample Identification Forms. Columns (10) – (36) are to be filled in by the
analyst(s) whom the work has been assigned (see Work Assignment Register).
The format also includes primary data validation requirements in columns (37) –
(53). The laboratory in-charge shall perform these validation checks as the analysis of a
sample is completed. In case the analysis results do not meet any one of the validation
checks, whenever possible, the analysis should be repeated. She/he would also fill in
Columns (54) – (55).
The results of the laboratory analyses shall be entered from these records in the
data entry system.
7 Concluding Remarks
Water quality monitoring is a team work. Right from the preparatory work before
proceeding for sampling till data validation and reporting to the District Data Centre, the
activities are to be harmonised with a professional finish.
Collection of samples being the most crucial among the chain of activities, it shall not be
left in the hands of un-skilled / casual staff as the entire monitoring programme and data
generation hinges on representative sampling. The person collecting samples should have
the application of mind in deciding, under the changing circumstances in the field, about
the correct and representative point of sampling. Any variation in field conditions, which
may have a bearing on the data generation and analysis, has to be recorded in the sample
identification form with reasoning.
20. 16
Figure 2 Data record and validation register
Data record Laboratory / organisation Laboratory code
Field determinations General Nutrients Org matter Alkalinity Hardness Major ions Other inorganics Coliforms Biol
LabsampleNo
Stationcode
Dateofcollection
pH
EC,µmho/cm
DO,mg/L
Temp,
o
C
Colour,code
Odour,code
pH
EC,µmho/cm
TDS,mg/L
TSS,mg/L
NH3,mgN/L
NO2
-
+NO3
-
,mg
N/L
TotalP,mg/L
BOD,mg/L
COD,mg/L
Phen,
mgCaCO3/L
Total,
mgCaCO3/L
Total,
mgCaCO3/L
Ca
++
,
mgCaCO3/L
Ca
++
,mg/L
Mg
++
,mg/L
Na
+
,mg/L
K
+
,mg/L
Cl
-
,mg/L
SO4
--
,mg/L
CO3
--
,mg/L
HCO3
-
,mg/L
Si,mg/L
F
-
,mg/L
B,mg/L
Total,
MPN/100mL
Faecal,
MPN/100mL
Chlorophyll-A,
µg/L
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (29) (30) (31) (32) (33) (34) (35) (36)
Data validation
Cations Anions Ion balance EC bal
Carbon
bal
CO3
--
bal Verification criteria Checked by Remarks
LabsampleNo
Stationcode
Ca
++
,meq/L
Mg
++
,meq/L
Na
+
,meq/L
K
+
,meq/L
Totalcations
Cl
-
,meq/L
SO4
--
,meq/L
CO3
--
,meq/L,
HCO3
-
,meq/L
NO2
-
+NO3
-
,meq/L
Totalanions
{(41)-(47)} / {(41)+(47)} (39) / (42) (12) / (11) (18) / (17)
If (10) < 8.3,
is (19)=0 ?
(1) (2) (37) (38) (39) (40) (41) (42) (43) (44) (45) (46) (47) (48) (49) (50) (51) (52) (53) (54) (55)
(48) < 0.1
(49) = 0.8-1.2
(50 ) = 0.55-0.9
(51) > 1
(52) = yes
21. 17
PERIODIC REVIEW OF SURFACE WATER QUALITY
MONITORING PROGRAMME
Er. S. C. Chadha*
1. Introduction
Surface water quality monitoring programme comprise several components and range of
purposes, like (1) designing of the monitoring network following some rationale and
categorisation of the monitoring stations depending upon quality requirements, (2)
identification of the location for representative sampling, (3) finalising the frequency of
monitoring and the parameters for analysis, (4) transportation of samples to laboratory
after analysis of some of the field parameters and preservation of samples for analysis of
the remaining parameters in the laboratory, (5) Standardising the analytical procedures,
(6) data validation, (7) imposition of analytical quality control procedure for reliability in
data generation, (8) data storage and interpretation, and (9) dissemination of information
on water quality to data users for formulating action programmes to protect the
wholesomeness of the water bodies and to meet the quality requirements to sustain
various designated-best-uses. Hence, the functional elements are multi-disciplinary in
nature and need to be harmonised for a concerted effort in generating reliable water
quality data, so that the data user agencies are not at fault while drawing Action Plans for
conservation of the quality of this scarce resource.
2. Need for Periodic Review of the Monitoring Programme
The river regime being an ever-changing dynamic system and so also being the land use
………………………………………………………………………………………………
.* Director, River Data Directorate, Central Water Commission, New Delhi-110 066
22. 18
pattern in a fast-developing country, like India, there is a need for periodic review of all
the elements of the monitoring programme mentioned above. This is also necessary as the
interpretation of the water quality data may reveal strengthening of monitoring
programme in terms of more frequent sampling for surveillance, additional parameters
for analysis, improved methods of analysis with state-of-the-art instruments for greater
accuracy and precision to improve upon reliability in data generation etc. Besides, there
may be necessities of having conjunctive studies on pollutant travel from surface to
groundwater or vice-versa with the groundwater monitoring agencies and pollution
control boards at the Central and State levels.
The “Hydrology Project” under the Ministry of Water Resources, Government of India, is
for capability development of the Central and State Surface Water and Groundwater
Agencies in water quality data generation as a part of the national “Hydrological
Information System” (HIS) being developed under the Project, a mechanism has to be
evolved for concerted effort in water quality monitoring programme through mutual
discussion among the participating agencies for problem-solving and for sustenance of
the programme even after the Project comes to an end.
3. Water Quality Monitoring and Co-ordination
Deliberations have already been held at the four regional level technical meetings on the
recommendations of the State agencies participating in the Hydrology Project, and it was
decided that the Sate-level Review Committees may discuss common
problems/constraints for trouble shooting. The Committees will also review the locations
of monitoring stations, need-based location-specific parameters and frequency of
monitoring, co-ordination among State agencies to avoid duplication of efforts in WQ
23. 19
monitoring, data analysis and interpretation, data management, faster communication and
availability of data, analytical quality control among HP-laboratories etc. Data user
agencies, within the scope of the Hydrology Project, have a provision under the
Hydrological data user group meetings for interactions and feed back from user
organisations. All project agencies are expected to formulate Hydrological Data User
Groups (HDUG). A similar group for water quality may be essential. The memberships
could comprise representatives from the following agencies:
• Central Water Commission (CWC)
• Central Ground Water Board (CGWB)
• Central Pollution Control Board (CPCB)
• State Pollution Control Board (SPCB)
• State level HP agencies
• Nodal Officers of the State
• Regional Data Centres of the State and CWC
• User agencies from educational and research institutes
The modalities of the membership, terms of reference, frequency of the meetings and
scope may be discussed and finalised. The State level committees which may be statutory
in nature, as recommended in the regional level meetings, may also be discussed.
4. Concluding Remarks
The proposal for constitution of the water quality data user group meetings and the State-
level Committees is based on the premise that the monitoring agencies have
understanding of the programmes of the member agencies through mutual exchange
/dissemination of information besides having a unified procedure for monitoring in the
24. 20
management of surface water quality. The member agencies could also initiate
investigative studies of common interest to strengthen the monitoring programme without
duplicating efforts for the common cause.
Such Committees can bring in transparency in the monitoring programme for the
development of a reliable database on water quality through mutual help without being
solely dependent on external technical support.
Note : The views expressed are for deliberations only and not of the Central Water
Commission, Government of India.
25. 21
Data Validation and Analysis
M. Villars*
1.1 Introduction
Validation of water quality data involves checking and assessment of the data to see
if there have been any errors made during sampling or analysis of the water quality
sample.
Definition
Water quality data validation consists of a series of checks to see if errors have been made in
water sampling, sample analysis or data entry.
Standard checks should be applied to test the data. These usually involve the
application of check readings for errors in time and magnitude. While many of the
data validation checks can be made by hand, the checks are also built into the
database software. The advantage of computer validation techniques are that they
are objective and uniform. Data from all sources are subjected to the same scrutiny.
The computer also allows the use of checking algorithms which can be tedious to
apply manually.
One another important organizational aspect of validation is the possibility of splitting
data validation tasks between field centres equipped with data entry microcomputers
and the central data processing computer. Since most microcomputers have
standard data entry software packages that incorporate data validation options, no
software development effort is required. Fields validation checks could include
absolute checks for dates and variable codes, and relative checks for range and rate
of change. Tables and plots of input data could also be made for manual checking.
Such a system would reduce considerably the error rate of data arriving at the centre
where more elaborate validation, e.g., inter-station consistency checks, could be
performed.
1.2 General Procedure for WQ Data Validation
Water quality data validation should be conducted in part by the chemist at a water
quality laboratory, and in part by the water quality experts at the regional or district
data centers.
The laboratory chemist will enter analytical results and field observations into the
laboratory record sheet. This sheet includes a number of a validation checks to be
conducted. I the future, the data will be entered into the computer database using the
Data Entry Software (SW DES for WQ). This is currently under development. Most of
the validation checks will be made by the database software.
Once the data has been checked, any signalled errors should be corrected if
possible. This may require new analysis of some samples. The validated data will be
sent by diskette from the laboratories to the regional data centre, where they will be
added to the water quality data base.
* Consultant, Hydrology Project, CSMRS Building Olof Palme Marg Hauz Khas New Delhi-110016
26. 22
Further validation of data will take place at the data centre, where the latest data
entries can be checked compared to the historical data.
1.3 Specific Data Validation Tests
A series of data checks should be carried out to identify any problems in the data. A
number of tests is described below including:
• Absolute checking/Data entry
• Checking if data is within the detection limits of a particular method
• Checking if the data is within the expected ranges for a parameter
• Checking if there are too many (or too few) significant digits reported
• Checking if data are physically or scientifically possible (general checks)
• Checking correlation of parameters (Some conditional checks)
• Checking the correlation between EC and TDS
• Checking the cation-anion balance
Absolute checking/Data entry
Absolute checking implies that data or code values have a value range that has zero
probability of being exceeded. Thus, geographical coordinates of a station must lie
within the country boundary, the day number in a date must lie in the range 1-31, and
in a numeric-coding system the value 43A cannot exist.
The limits used may take one of the following forms:
• A single absolute value or range;
• A set of ranges applicable in different areas and/or at different times
• Ranges applicable to many stations or ranges which are applicable only to
individual stations.
Data failing these tests must be incorrect. It is usually a simple task to identify and
remedy the error. The database software should be programmed to catch these
types of errors during data entry.
Detection Limits
The water quality results reported cannot be less than the detection limit of the
analytical procedure being used to measure the concentration. Thus all data should
be checked compared to the expected detection limit. The detection limits of all
analytical procedures must be known. If there are different procedures possible for
making an analysis, the procedure that is used must also be known.
Checking WQ data against expected ranges
Water quality data can also be checked against expected ranges. For the parameters
being measured in HP, typical ranges for surface water are known (Table 2).
27. 23
Table 2 Some typical values for composition of surface water
Constituent Unit
Concentration Range
Temp °C 10-35
PH - 6-9
EC µS/cm 250-5000
Na+
mg/l 5-75
Significant Digits
The number of significant digits to be reported for a water quality result depends on:
• the precision of the analytical procedure used
• the absolute value of the result compared to the range of expected results
General Checks
General checks are made to see if the water quality results are physically or
scientifically possible.
A simple general check is that the totals of any variable must be greater than the
component parts as in the following examples:
• Total coliforms must be greater than faecal coliforms
• Total iron must be greater than dissolved iron
• Total phosphorus must be greater than dissolved (ortho-)phosphorus
• Total iron must be greater than dissolved iron
General checks:
Total solids ≥ Total dissolved solids
Total solids ≥ Total settleable solids
COD > BOD
Total Coli ≥ Faecal Coli
Total Iron ≥ Fe+2
, Fe+3
Total P ≥ PO4-3
EC (µS/cm) ≥ TDS (mg/l)
Total oxidized nitrogen ≥ Nitrate, nitrite
Total oxidized nitrogen = Nitrate + nitrite
Total hardness = Ca hardness + Mg hardness
Some conditional checks: correlation of parameters
When there are known correlations between one or more water quality parameters these can
be used to
Some of the more well known correlations between parameters are:
• Total dissolved solids and specific conductance
• pH and carbonate species
• pH and free metal concentrations
• Dissolved oxygen and nitrate
28. 24
Conditional checks
If pH > 6 then Al+3
< detection limit
If pH > 6 then Mn+2
< detection limit
If pH < 8.3 then CO3
-2
=0
If DO (mg/l) = 0 then NO3
-
=0
If DO (mg/l) > 0 then NO3
-
>0
If DO (mg/l) > 7 then Fe+2
=0
Correlation between EC and TDS
The numerical value of Electrical Conductivity (EC) in µS/cm should be higher than
that of Total Dissolved Solids (TDS) in mg/l. It is recommended that conductivity be
plotted against TDS and values lying away from the main group of data be checked
for errors. The relationship between the two parameters is often described by a
constant (commonly between 0.55 and 0.7 for freshwaters).
Thus: TDS (mg/l) ~ 0.6 x EC (µS/cm)
The value of the constant varies according to the chemical composition of the water.
TDS and Conductivity
For freshwaters, the normal range of TDS can be calculated from the following relationship:
0.55 conductivity (µS/cm) < TDS (mg/l) < 0.7 conductivity (µS/cm)
Typically the constant is high for chloride rich waters and low for sulphate rich waters.
Cation-Anion Balance
When a water quality sample has been analysed for the major ionic species, one of
the most important validation tests can be conducted: the cation-anion balance.
The principle of electroneutrality require that the sum of the positive ions (cations)
must equal the sum of the negative ions (anions). Thus a cation-anion balance can
be written:
If significant errors in any of the major ion analyses has been made there will be an
error in the cation-anion balance. If this error is too large (>10%), it indicates that
there has been a error made in at least one of the major anion analyses.
Cation-Anion Balance
∑ cations = ∑ anions
where:
cations = positively charged species in solution (meq/l)
anions = negatively charged species in solution (meq/l)
29. 25
For GW and surface water, the % error should be less than 10%
Ion balance (example)
A laboratory measures the following concentrations:
Cation Conc (mg/l) Anion Conc (mg/l)
Ca+2
93.8 HCO3
-
164.7
Mg+2
28.0 SO4
-2
134.0
Na+
13.7 Cl-
92.5
K+
30.2
1. First the concentrations of cations and anions must be converted from mg/l to
meq/l.
(a) This conversion is made using the mg/meq value for each major ion species. This
value is equal to the atomic weight of the species divided by the ion charge.
For Calcium (Ca+2
):
• atomic weight = 40
• ion charge = 2
• mg/meq = 40/2 = 20
(b) Dividing the concentration (mg/l) by the mg/meq value for each species results in
meq/l.
For Calcium (Ca+2
):
• Concentration (mg/l) = 93.8
• mg/meq = 20
• 93.8/20 = 4.69 meq/l
Percent Balance Error
∑cations - ∑anions
% balance error = ------------------------ x 100
∑cations + ∑anions
cations = Na+
+ Ca+2
+ Mg+2
+ K+
(in meq/l)
anions = Cl-
+ HCO3
-
+ SO4
-2
(in meq/l)
30. 26
(c) A table should be completed with all the values per species, and the sum of
cations and anions.
Cation Concentration
(mg/l) (mg/meq) (meq/l)
Ca+2
93.8 20.0 4.69
Mg+2
28.0 12.2 2.3
Na+
13.7 13.7 0.60
K+
30.2 39.1 0.77
Total Cations 8.36 meq/l
Anion Concentration
(mg/l) (mg/meq) (meq/l)
HCO3
-
164.7 61.0 2.74
SO4
-2
134.0 48.0 2.79
Cl-
92.5 35.5 2.61
Total Anions 8.14 meq/l
2. Check accuracy (% balance error)
∑cations - ∑anions
% balance error = ------------------------ x 100
∑cations + ∑anions
8.36 – 8.14
= --------------------- x 100 = 1.3%
8.36 + 8.14
This is less than the allowed error, so the sample results can be accepted.
If % error > 10% then check results, and possibly re-analyse samples.
Note: An accurate ion balance does not necessarily mean that the analysis is correct.
There may be more than one error and these may cancel each other out.
1.4 Aspects of Data Analysis
The water quality data collected are the basis of the information that can be provided.
However, the data themselves are not ‘information’. If data are not in a form which
can be used or understood by its intended recipients then they cannot be considered
to be information. The process of data analysis involves abstracting, transforming,
summarising and commenting on the data so that they will be useful to those to
whom they are ultimately transmitted.
In order to make a conversion of data to information, the data need to undergo some
form of analysis. Such analysis may be simple, for example, the calculation of
elementary statistics or the production of graphical output, or may be more complex
involving advanced statistics or mathematical modelling.
31. 27
The specific analyses to be conducted depend on the water quality information
desired, or the specific questions about water quality being asked. Water quality
concerns are wide and varied, but probably the most commonly asked questions are:
1. What is the water quality at any specific location or area?
2. What are the water quality trends in the region: is the quality improving or getting
worse?
3. How do certain water quality parameters relate with one another at given sites
4. For surface water (rivers): how do certain water quality parameters relate to
stream discharge?
5. What are the total mass loadings of materials moving in and out of water
systems, and from what sources and in what quantities do these originate?
6. Are sampling frequencies adequate and are sampling stations suitably located to
represent water quality conditions in an area?
It is now possible to carry out many of the techniques described below on a computer
running a proprietary statistical software package. However, it should be borne in
mind that such an approach carries with it dangers for the inexperienced. With a
computer package it is possible to generate any number of statistics from a set of
data with no regard to their appropriateness. Care should be exercised if this method
is contemplated, therefore.
1.5 Types of Data Analysis
It is often the case that those who receive, and may need to act upon, water quality
data are non-technical people. Often managers, politicians or members of the public
need to comment or make decisions based upon water quality data. Unless such
people are technically qualified, data alone will not of any use to them; they need to
know what the data means.
There are a number of ways that water quality data can be made more meaningful to
a non-technical audience including the following:
• comparing the data with national water quality standards - this gives an insight
into the scale of a particular data set (e.g., if the data show that a particular
groundwater sample contains a higher concentration of pollutant than is
allowed by a national drinking water standard, most people would assume that
it may not be safe to drink this water)
• comparing the data to international standards - it may be useful to compare the
data to standards used by other countries (e.g., the United States) or
international organisations (e.g., the World Health Organisation or the
European Union) particularly if standards for a particular pollutant have not
been defined nationally
• calculating water quality indices, such as Water classification index or S.A.R.
• determining the water quality classification and comparing to desired
classification
• comparing the data derived from one area to data from another similar area -
for example, it is easy to see how two similar rivers compare in terms of their
pollution load when their water quality data are presented together
• calculation of trends showing how water quality has changed at one or more
sampling points either over time or due to a particular event (e.g., the
construction of a power station on a river reach)
32. 28
• calculating how much mass of a substance has travelled down a river (i.e.
mass fluxes).
1.6 Water Classification Index for surface waters
In India, several water quality indices can be calculated which indicate the suitability
of water for different uses:
• Water classification index for surface waters
• Sodium Absorption Ration (SAR) for irrigation suitability
• Percent Sodium for irrigation suitability
• Residual Sodium Carbonate – for irrigation suitability
• Chloride – bicarbonate ratio
• Wilcox
• Pipers Tri-linear plotting
The a water classification index for surface waters has 5 categories and is used to
indicate water quality required for different uses.
The Central Pollution Control Board has classified the inland surface waters into 5
categories - A to E on the basis of the best possible use of the water as shown in
Table 1. The classification has been made in such a manner that the water quality
requirement becomes progressively lower from class A to class E.
A water body may be subjected to more than one organised use. The use demanding
the highest quality is the designated best use. A water body or stretch of river whose
existing water quality does not meet the designated best use criteria requires action
to mitigate the situation. Based on such analysis river action plans are formulated.
The results from the water quality monitoring should be used to calculate the water
quality index, and to check with the designated use of that water body.
1.7 Graphical techniques
Many of the above techniques are considerably enhanced if the data are presented
graphically. However, care should be taken to ensure that the graph type is chosen
to clearly transmit the necessary information (see above).
There are a number of advantages associated with the data analysis using graphical
techniques as follows:
• trends in the data are often easier to spot
• outlying data points are normally obvious
• many people find visually presented data more acceptable and more readily
understandable
It is important when presenting data graphically that:
• all graphs are easy to read and understand - in particular the temptation to put
too many data sets onto one graph should be avoided; it is better to present this
information using more than one graph, if necessary.
33. 29
Table1 Primary water quality criteria for various uses of fresh water
Designated best use Class Criteria
Drinking water source
without conventional
treatment but after
disinfection
A 1. Total coliform organisms MPN/100mL
shall be 50 or less.
2. pH between 6.5 and 8.5
3. Dissolved oxygen 6 mg/L or more
4. Biochemical oxygen demand 2 mg/L or
less
Outdoor bathing (organised) B 1. Total coliform organisms MPN/100mL
shall be 500 or less
2. pH between 6.5 and 8.5
3. Dissolved oxygen 5 mg/L or more
4. Biochemical oxygen demand 3 mg/L or
less
Drinking water source with
conventional treatment
followed by disinfection
C 1. Total coliform organisms MPN/ 100mL
shall be 5000 or less
2. pH between 6 and 9
3. Dissolved oxygen 4 mg/L or more
4. Biochemical oxygen demand 3 mg/L or
less
Propagation of wild life,
fisheries
D 1. pH between 6.5 and 8.5
2. Dissolved oxygen 4 mg/L or more
3. Free ammonia (as N) 1.2 mg/L or less
Irrigation, industrial cooling,
controlled waste disposal
E 1. pH between 6.0 and 8.5
2. Electrical conductivity less than 2250
micro mhos/cm
3. Sodium absorption ratio less than 26
4. Boron less than 2mg/L
5. Percent Sodium less than 60
• the scale of the axes used is such that the data cover a large percentage of the
graph
• all graphs are clearly titled and each axis, and if appropriate each data set, is
clearly labelled
34. 30
There are a number of types of graph which can be effective in presenting water
quality data as detailed below. The choice of graph will depend upon a number of
factors including the information required from the plot, the intended audience and
clarity and ease of use considerations. It is often the case that the choice of graph
can only be finally decided by actually plotting a number of different types of graph
and assessing them for effectiveness.
Time Series Graphs
A graph in which water quality data (on the ‘y’ axis) are plotted against time (on the
‘x’ axis) in units which will depend on the frequency of sampling. This type of plot
helps to identify trends or cyclic patterns in the data and is also a good way of
identifying outlying data points.
Time series graphs are also useful for spotting connections between two or more
water quality variables. If it is suspected, for example, that the biochemical oxygen
demand in a river reach increases when the suspended solids load increases, an
effective way of checking this can be to plot both of these variables on a time series
graph. Visual inspection can then be used to see if peaks and troughs for the two
variables coincide.
Histograms
Histograms or bar charts are effective at displaying the relative differences in data.
That is, it is easy to show that a sampling point has twice the pollutant concentration
of its neighbour by means of a histogram.
Histograms are also useful for displaying data for a non-technical audience as they
are easily understood by the majority of people.
Pie Charts
Pie charts, which are circular diagrams divided into a number of segments, are less
frequently used for water quality data. They are used when it is necessary to present
information about the relative proportions of a particular parameter, however. For
example, the relative proportions of a pesticide which were dissolved in water, bound
to suspended solid particles or present in the bottom sediments of a river could be
represented using a pie chart.
Profile Plots
A plot of water quality data down the length of a river (longitudinal profile) can be
useful for observing changes which occur as the river flows downstream. Often such
plots are annotated with the positions of major discharges and river tributaries so that
the effect of these inputs is clearly visible on the graph.
If samples have been collected at various depths, a vertical profile of the data can be
plotted. Such plots are often used to analyse how lake water or groundwater varies
with increasing depth.
Geographical Plots
It is often useful to plot water quality data on a map base to show local and regional
variations in water quality. Such a technique can be used to attempt to pinpoint a
35. 31
pollution source from groundwater data or merely to show how one river or
catchment compares to another in terms of its water quality or pollution load.
Advanced Techniques
In addition to those methods of data analysis given above there are also a number of
more advanced techniques which can be used. Although, a complete description of
such techniques is outside the scope of this document, there follows below a brief
outline of some of the methods available:
• linear trend analysis - although this can be done simply by plotting data on a time
series graph (see above), it is also possible to analyse trends through the use of
sophisticated statistical analyses; trend analysis can be important for the
analysis of water quality data as it can aid understanding of the variability of data
and also allow predictions to be made of likely future water quality
• regression and correlation analysis - regression and correlation analysis are
related techniques which are used to assess the association between two or
more variables; both can be useful techniques for establishing the factors which
regulate the variability of a particular water quality parameter.
• autocorrelation analysis: to assess the association between two or more
measurements of the same variable at different times.
• hypothesis testing: Statistical analysis to check for relationships within the data
(e.g. a step trend)
• mathematical modelling - a technique for representing and predicting, by means
of mathematics, the behaviour of a system; mathematical models can be useful
predictive and policy testing tools in that they allow operators to forecast the
behaviour of a water body which will occur following some future change to the
system
It is important to remember that the above techniques, whilst extremely powerful
when used correctly, can lead to false conclusions and, therefore, poor management
decisions if used by the inexperienced. It is often advisable, therefore, to use the
simplest data analysis technique which will adequately perform the required task.
36. 32
Design of Water Quality Yearbook
Dr. Roop Narain*
Dr. S. P. Chakarbarty**
Er. Devendra Sharma***
Introduction
Data is a base for planning of any project. The process of collection of data has been
in progress since time immemorial. The data has been collected for specific purposes, used
for the purpose, changed in to reports & filed. At present the data is scattered in different
organizations & laboratories. This has been quite expensive, as time and money has been
spent on collection of same type of data. However old data can be of historical importance &
a useful guide to understand the action of various forces, which may be responsible for
present status.
Collection of data on the quality of water
Central Water Commission being a central organization under the Ministry of Water
Resources has to think in terms of the national perspective on utilization of resources. The
collection of hydrological data, by the default definition includes the data on quality of water.
As is well known, the data collected by Central Water Commission is very thorough in
respect of location, depth, time, velocity and distance from the reference point from the bank;
a considerable amount of time and money is involved in this process of data collection.
Keeping in view that quantity without quality may be meaningless, Central Water
Commission is also collecting the data on the quality of water at all such important locations.
For collection of data on the quality of water, Central Water Commission has also
established a large network of laboratories almost in all the states of India. Depending upon
the level of data to be collected, these laboratories have been equipped with the adequate
*Research Officer, Hydrological Observations Circle (Noida), Central Water Commission,
Research Unit, B-5, Kalindi Bhawan, Qutub Institutional Area, New Delhi – 110 016
**Consultant, Hydrology Project, CSMRS Building, Olof Palme Marg, N Delhi–110 016
*** Superintending Engineer, Hydrological Observations Circle, Central Water Commission,
C-130, Sector 19, Noida,
37. 33
level of equipment and the laboratories have been designated as level I, level II and level III
laboratories. The level I contains equipment suitable for observing the data on parameters
which must be observed in situ i.e. without any time lag between the collection and analysis.
The level II contains equipment suitable for observing the data on parameters which must be
observed with more sophisticated equipment and can be done within 6-24 hour of collection
of sample. For this purpose, the samples are kept under near freezing condition to keep the
bacterial and other physico-chemical reactions at the minimum activity.
The level III contains equipment suitable for observing the data on parameters, which
need sophisticated and state of art equipment. The equipment in such laboratories are quite
costly and need expert personnel for their operation. In view of the cost involved and to
observe economy at the national level, such laboratories are kept in Northern, Eastern and
Southern Regions. Therefore such laboratories can also be termed as regional laboratories.
Central Water Commission has already done this investment and the data is being collected
on various parameters covering general physical, chemical and biological parameters. The
data on trace metals and trace organic pesticide, herbicides and insecticides is also being
collected.
Nature of data
The nature of data that can be stored can comprise of physical, chemical and
biological nature. The parameters covering these aspects are given in annex 1. As the
analysts are generally proactive, it is not necessary that all samples be analyzed for all
parameters. That should depend upon the nature of sample and its immediate requirement.
Having established such a large network of collection of hydrological data, it goes
without saying that a small part of time of the personnel employed at the basic data collecting
centers can also be utilized for collection of information on factors which may have a bearing
on the quantum of various parameters. Some of such factors have been listed below. (Details
in annex –II)
1. Climate
2. Geology/Morphology
38. 34
3. 10 year hydrology data (average of monsoon/non monsoon)
4. Agricultural practices
5. Various projects dams canals transfer inter basin.
6. Forest, semi arid, arid and mountain regions.
7. Population in villages, towns and cities.
8. Industries small, medium and large (In particular having solid and liquid wastes)
9. Quantum of water used & return flows
10. Health aspects on population – Hospital/Diseases.
11. Various flora and fauna – spatial distribution.
12. Reaches showing visible /invisible impacts.
13. Correlation with ground water quality with in 5 km radius.
As the qualified personnel having a very good academic and scientific background
will collect the data on such aspects, the data will be very authentic and can be relied upon
for doing modeling and other studies. The cost of collection of such data will also be very
low in terms of manpower and other expenses
For examining the quality of water for various uses, the biological oxygen demand
and bacterial presence or absence is also essential especially the coliform type as some of the
coliforms are typically found in the intestines of animals including anthropoids. These are
characterized by their prolific growth even at 45° Celsius. To examine the number of
bacteria, these are allowed to grow in a special nutrient medium. When they form colonies,
their number is counted under magnification. With powerful microscope, this can be done by
isolation bacteria and staining them with suitable chemicals. The shape, size and their
number can be easily recorded with very little extra effort. For this, equipment has already
been procured in one of the Regional laboratories. As the information on the presence of
various trace metals and other chemicals in trace quantities is being collected, it may not be
difficult to link the presence of various tiny flora and fauna, including bacterial population
with the trace metals chemicals and various factors connected with climate and ecology.
Such correlation can be of immense help in linking degenerative and mutagenic changes in
the life processes. It may not be out of place to mention that the changes take place faster in
the species, which have a short life span and multiply rapidly under a given condition.
39. 35
Quantum of data
However all these data with different frequencies, locations and timings will make it
quite bulky even if taken for one year and individual values, except the extremes may not
serve much purpose. However for reference one or two hard copies of daily data may be
essential. For evolving any logical conclusion, the combination of some values and their
statistical averages over different seasons may be useful. However some of the data such as
odour, which cannot be converted into some numerical form for arriving at averages can be
kept as such or attempt can be made to convert such information in to numerical forms.
Processing of data
Processing such large magnitude of data from hard copy (printed book) will also
involve large number of man-hours. For wide circulation of data, it may be a fit case to
present the averages and the trends, which can be statistically arrived, form the data. The
demand from such users can be easily met if the data is properly stored in a format, which
can be processed with suitable software to extract the relevant figures over a large time
period. The general aspects can be summarized in one to two pages.
Users
The data of this type can be utilized for diverse purposes depending upon the
immediate requirement of the user e.g.
1) Organizations needing the suitability of data for power plant (cooling purposes) need
not be interested in colour/odour, climates, trace metals and pesticides, bacterial
population etc.
2) Organizations for bathing need not worry on trace quantities of minerals and organics.
3) Water softening plants may not be very keen on bacteriological, suspended impurities
and many other parameters except calcium & magnesium.
40. 36
4) Recreational users may worry only on colour, odour, floating and suspended matter etc.
5) Agriculturist may more interested in Sodium Adsorption Ratio, Sodium Percentage &
Electrical Conductance.
6) Municipal authorities may worry more about trace metals, organic and suspended
impurities and bacterial population.
7) An environmentalist may be more keen an appearance of disappearance of flora and &
fauna and their numbers.
8) School & college students may be interested in general parameters.
9) Water storage authorities may be more interested in sulfate, chloride and BOD values.
10) Doctors may be more interested in sodium, nitrate and fluoride etc. which are not
removed by the conventional treatment methods.
11) NGOs may worry about all aspects concerned with social life.
12) Pollution control agencies may concentrate on trends to prevent deterioration of quality
Publication of data
Presently Central Water Commission publishes such data on annual basis as Water
Quality Yearbook on the lines of its Water Year Book and sediment Year Book. As most of
the data was used in-house and the demands from other users were few and far between,
these could be met easily, hence it was not thought necessary to give wide publicity to the
data. However in recent years the demand from other users has increased and causes
inconvenience in copying of data from the few published copies, it would be in the interest of
Central Water Commission to publicize such data for the benefit of various users. It would
also eliminate unnecessary repetition in collection of data or data with inadequate method of
collection is minimized and the good quality data remains for reference. In doing so, the
Central Water Commission can do a yeoman’s service to the nation and may save a
considerable cost on money and manpower. Various academic institutes and NGOs are
incurring such costs on the pretext of providing Ph. D degrees and for bringing more
awareness among general masses as well to gain publicity. The data collected by them is
mostly not according to the standard methods. In many of such instances, it is observed that
the conclusions drawn by them exceed all imaginations
41. 37
The format for storing data on quality of water
The format for storing the data has to be worked out very carefully to ensure that
most of the future demand on the data extraction can be easily met.
Each site should contain following information to cover.
1. General features of site, location, town, district, state, river- tributary, sub-tributary,
longitude & latitude etc.
2. Basin map showing site in appropriate scale
3. Climate, geology, morphology of site.
4. Hydrological features / storage / Return flows
5. Agricultural practices,
6. Forests: flora & fauna.
7. Population
8. Location and spread of various industries.
9. Data: All parameters should be available for recording
The data can have the following formats
a) Physical parameters
b) General chemical parameters
c) Biological
d) Trace metals and chemical
e) Microbiological
f) Computed indices
All these details on a data should have identical value for the following variables
• Date of collection
• Time of collection
• Distance from the bank
• Depth of collection
For wide circulation of data, it may be a fit case to present the averages and the
trends, which can be statistically arrived, form the data. The demand from such users can be
easily met if the data is properly stored in a format, which can be processed with suitable
software to extract the relevant figures over a large time period. The general aspects can be
summarized in one to two pages.The details should be upgraded on annual basis to provide
for various developmental activities.
42. 38
The format for Water Quality Yearbook
The format for publication of averages and trends should include all such parameters
that have bearing on general uses and also for special users. The following aspects can be
included.
Maximum, minimum and average values with the number of observations for
monsoon and non-monsoon seasons along with annual weighted average value in respect of
following parameters:
1. Temperature
2. Colour
3. Turbidity
4. pH
5. EC
6. DO
7. BOD
8. COD/TOC
9. Chloride
10. Nitrate
11. Sulpfate
12. Hardness
13. SP
14. RSC
15. Total Coliforms
16. Total Planktons
In respect of parameters such as trace metals, pesticides and special bacterial and
micro flora and fauna; total sum of their values in terms of total loading can be given. This
would require calculation of their mass from the values of concentration/ number and
discharge for each season. Such a presentation would eliminate the risk of exposure of the
classified data on discharge of rivers crossing national boundaries.
The format of Water Quality Yearbook is presented for consideration. A specimen is
given at annex-III
Graphical presentation of data on concentration of above parameters for the last 5-10
years can also be given for the ease of understanding.
43. 39
Annex 1
List of parameters
1. Temperature
2. Colour
3. Odour
4. Turbidity
5. pH
6. Conductivity
7. Dissolved Oxygen
8. Carbonate
9. Bicarbonate
10. Sulfide
11. Calcium
12. Magnesium
13. Sodium
14. Potassium
15. Chloride
16. Sulfite
17. Sulfate
18. Fluoride
19. Bromide
20. Iodide
21. Orthophosphate
22. Boron
23. Silica
24. Nitrate
25. Nitrite
26. Ammonia
27. Kjeldahl Nitrogen
28. Organic phosphorous
29. BOD
30. COD
31. Total Organic Carbon
32. Iron II
33. Iron III
34. Copper
35. Mercury
36. Strontium
37. Nickel
38. Aluminum
39. Manganese
40. Chromium III
41. Chromium VI
42. Lead
43. Arsenic
44. Cadmium
45. Zinc
46. Silver
47. Molybdenum
48. Selenium
49. Phenolic compounds
50. Zooplanktons
51. Phytoplanktons
52. Organophosphorous
pesticides
53. Organochlorine pesticides
54. Polycyclic hydrocarbons
55. Atrazine family pesticides
56. Total Coliform
57. Escherechia Coliform
58. Other bacteria
59. Radioactivity in water and
sediment
60. Adsorbed chemicals on
bottom sediments
61. Adsorbed chemicals on
suspended sediments
62. Total Hardness
63. Sodium Percentage
64. Residual Sodium Carbonate
65. Sodium Adsorption Ratio
66. Classification
44. 40
Annex-2
General features of Hydrological Observation station and its Basin
1. Type of soil & geological formation in the basin.
2. Nature & location of various ores in each Sub-basin basin and the nature of their
prospecting activity.
3. Major minerals found in topsoil & subsoil say up to 100 M.
4. Nature of various major industries in various sub catchments of the basin.
5. Quantity and quality of surface flows in sub catchments.
6. Quantity and quality of water used for inter basin and inter sub basin transfers.
7. Nature of vegetative dispersion in the sub catchments.
8. Area under agricultural activity.
9. Area under assured irrigation.
10. Various crops grown in the sub catchments.
11. The respective area under each crop.
12. Nature & quantity of various insecticides and pesticides sold in each year season wise in
each sub basin/basin.
13. Nature & quantity of various herbicides sold in each sub basin/basin.
14. Number of villages/towns/cities in each sub catchments.
15. Cattle population/ milch cattle population.
16. Total municipal water supply in each town and total quantity supplemented by private
water harvesting.
17. Quantities of return flow from municipality & industries.
18. Treatment facility installed/ in operation.
19. Industry profile with respect to use of water and discharge of liquid and solid waste.
20. Disposal pattern of solid & liquid waste.
21. Source of collection of above information.
22. Names of hospitals in sub basin/basin.
23. Major and minor endemic & epidemic problems.
24. Major birds species found in the region with their eating habits & change in behavior &
population (ornithologists)
25. Various type of water fauna in river & lake systems; seasons wise including major & minor
variety, eating and reproductive habits.
45. 41
26. Various type of bacterial population in different reaches. Season wise disease water borne
on basins of illness.
27. Various water flora in the region; season wise.
28. Recreational activities in water bodies.
29. Partially or fully closed sub basins
30. Hydel generation/ thermal power generation units.
31. Nature of spatial distribution of rainfall.
32. Number of storage reservoirs in the sub-catchments with their capacity.
33. Water supplies arrangement of each municipality.
34. Activities on reuse of water by industry and municipality.
35. Impact on ground water quality where water is reused.
47. 43
DISSEMINATION OF INFORMATION ON WATER QUALITY
Dr. Roop Narain+
, Dr. M. C. Dutta++
, Dr. S. P. Chakrabarti*, and Dr. R. C. Trivedi**
1. Introduction
Data on quality of surface and ground water are most sought after by individuals,
municipal bodies, students / scholars of academic institutions, pollution control
authorities and social reformers. While an individual is keen to ascertain the quality for
its potability before use, the municipal bodies are concerned to ascertain the degree of
treatment necessary to render it suitable for safe public water supply. While the
academicians look at it with interest for a variety of purposes, like establishing
correlations among its constituent quality parameters, validating ionic balance, modelling
of water quality for prediction of impact due to introduction of pollutants through
innovative computer application techniques etc., pollution control agencies look for the
trend for evolving strategy to maintain and restore quality of water resources by
containment of polluting sources and prevention and control of pollutants being
discharged into water bodies only after compliance with the standards. The non-
governmental organisations (NGOs) and the Social Reformers serve as the ‘watch dogs’
for the protection of societal interest. Under this scenario, it is evident that there is a need
for water quality data among various sections of the society, even if their interests could
be conflicting at times.
…………………………………………………………………………………………….
+ Research Officer, Research Unit, Head Office Circle, Central Water Commission, N. Delhi – 110 066
++ Research Officer, River Data Directorate, Central Water Commission, N. Delhi – 110 066
* Consultant, Hydrology Project Office, CSMRS-Building, 4th
Floor, Olof Palme Marg, N. Delhi-110 016
** Sr. Scientist, Central Pollution Control Board, Parivesh Bhavan, East Arjun Nagar, Delhi-110 032
48. 44
2. Water Quality Information
2.1 Water quality Data Generation
Water quality is being monitored by several agencies with specific objectives to meet the
requirements of the respective agencies in accordance with their mandates Although the
Central and the State surface water (SW) Departments are concerned are charged with the
responsibility of developing water resources with no apparent concern about the quality
aspect of the resources, it is inherently implied that the quality of the water resources
developed is good enough to qualify for meeting the needs of various designated-best-
uses prevalent all along the river stretch. The Central and the State Pollution Control
Boards are to observe that the wholesome quality of the natural waters are maintained or
restored, if required, to sustain the prevalent uses. There is, therefore, an unwritten
interdependency among the agencies involved in the task of water quality management,
which can seldom be ignored. Hence, there is a sincere need for frequent interaction and
sharing of information among the agencies.
2.2 Water Quality Database Development
Under the “Hydrology Project” taken up by the Ministry of Water Resources, the water
quality database is being created at national and State levels as a part of the Hydrological
Information System (HIS) being developed. After primary data validation at the
laboratory, the data will be processed at the Sub-divisional / Divisional Data Processing
Centres for secondary validation, following a designed format for data entry in a unified
manner by all the agencies participating in the programme. and thereafter for storage at
the State / Regional / National level to generate the database to be available for the user
agencies.
49. 45
2.3 Interpretation of Data for Information Generation
To render the validated data useful for the concerned agencies in planning of Action
Programmes in a holistic manner and for their implementation, the data are to be
analysed and interpreted for generation of information. This requires presentation of
data in the form of charts. To meet the needs and purposes of the data user agencies
and the society at large, it is imperative on the part of the generator(s) of data to
publish “Annual Report on Water Quality” for dissemination of information in a
simplistic manner, especially through graphic presentations or easy-to-read maps,
with interpretations. Otherwise, it will remain stockpiled in individual organisations
with no apparent use after incurring considerable expenses in collection,
transportation, and analysis of samples in sophisticated instruments.
3. Annual Report on Water Quality
Annual Report on water quality, therefore, should contain river basin / water shed-
wise information in terms of the following elements:
Brief introduction of the basin with a map in appropriate scale indicating the
location of monitoring stations with station code
Water quality status: Desired quality to sustain designated-best-uses in various
reaches;
If such information are not available with CWC, conjunctive efforts may be made
with CPCB, to have a uniform database. The concept is already well-developed,
and all major rivers with their principal tributaries have been classified into five
50. 46
categories of designated-best-uses in consultation with the State agencies. The
categories of designated-best-uses are as follows:
Class A - Drinking Water Source after only disinfection
B -Outdoor bathing and contact water sport
C - Drinking water source after conventional treatment including
disinfection
D - Propagation of wildlife and fisheries
E - Agriculture, industrial cooling & controlled wastewater disposal
• Existing water quality status as observed from monitoring in terms of the
criteria parameters defined by CPCB for sustenance of the aforesaid uses; and
• Critical parameters to be taken note of for protection of quality
Analysis of data to establish spatial trend of water quality from preceding five
years (say) in terms of Indicator parameters depicting the health of the river. This
would require graphical presentation of the data for ease in understanding.
Development of correlations among parameters for better understanding of the
quality and for validatory checks in building up confidence in analysis and data
reliability
51. 47
Identification of hot spots (stretch-wise) wherever the actual/existing quality falls
below the desired quality. Such information will help the pollution control boards in
planning strategies for strengthening their enforcement programmes.
4. Concluding Remarks
The surface water regime being a dynamic system, the monitoring programme needs
periodic review atleast after every five years to decide on location of stations, parameters,
frequency of sampling, instrumentation and method of analysis, training need for
laboratory personal.
Interaction with concerned agencies involved in surface water quality monitoring is
essential in view of rapid development in the field of instrumentation techniques in water
quality analysis and also interdependency of the agencies in formulating Action
Programmes with a holistic approach in a co-ordinated manner besides dissemination of
information for the benefit of the society in providing quality water
Reference:
Water Quality Status & Statistics (1995), Monitoring of Indian National Aquatic
Resources Series / MINARS / 12 / 1997, Central Pollution Control Board, Govt of India,
1997.
52. 48
Quality Assurance Programme
A. K. Mitra*
1. Introduction
The objective of a water quality monitoring programme is to produce data and information on
the quality of water resources, so that appropriate management can take place. All steps
within the monitoring programme must be designed to produce the desired data and
information, with sufficient quality.
The goal of a laboratory Quality Assurance Programme is:
• To ensure meaningful water quality assessment
• To have confidence in results, based on standardized procedures for all components of
water quality monitoring
2. Components of Quality Assurance Programme
The QA programme for a laboratory or a group of laboratories should contain a set of
operating principles, written down and agreed upon by the organisation, delineating specific
functions and responsibilities of each person involved and the chain of command. The
following sections describe various aspects of the plan.
Sample control and documentation: Procedures regarding sample collection, labelling,
preservation, transport, preparation of its derivatives, where required, and the chain-of-
custody.
Standard analytical procedures: Procedures giving detailed analytical method for the
analysis of each parameter giving results of acceptable accuracy.
Analyst qualifications: Qualifications and training requirements of the analysts must be
specified. The number of repetitive analyses required to obtain result of acceptable accuracy
also depends on the experience of the analyst.
Equipment maintenance: For each instrument, a strict preventive maintenance programme
should be followed. It will reduce instrument malfunctions, maintain calibration and reduce
downtime. Corrective actions to be taken in case of malfunctions should be specified.
Calibration procedures: In analyses where an instrument has to be calibrated, the procedure
for preparing standard solutions and making a standard curve must be specified, e.g., the
minimum number of different dilutions of a standard to be used, method detection limit (MDL),
range of calibration, verification of the standard curve during routine analyses, etc.
Quality control of the analytical data : Quality control may be either internal or external.
External QC is also called as Quality assessments. All analysts must use some QC as an
intuitive effort to produce credible results.
Data analysis : Data reduction, validation, and reporting are the final features of a QA
programme. The reading obtained from an analytical procedure must be adjusted for such
factors as instrument efficiency, extraction efficiency, sample size and back ground value,
i.ex
53. 49
before it becomes a useful result. Each result or a set of results must be accompanied by a
statement of uncertainty.
……………………………………………………………………………………………………………
………...
• Central Water Commission, Regional Office, Hyderabad
3. Quality Assurance in Water Quality Monitoring
The full set of activities for QA in WQM which should be documented are:
• monitoring network design,
• sample collection (including field measurements, bottle labelling, proformas, preservation,
treatment and transport.
• sample control and documentation in the laboratory
• maintenance of equipment
• laboratory AQC
• Data validation, reduction, and reporting
3.1 Monitoring network
Monitoring network is to designed depending on the objective of the programme. It may be
flexible.
3.2 Sample collection
Sample collection includes the following activities:
• collecting the sample in the correct manner, in the correct container
• field measurements of water quality: e.g. Temperature, pH, EC, DO
• labelling sample bottles and completing sample proforma
• preservation (if necessary) and transport to the laboratory
3.3 Collecting the sample
The person collecting the sample must know how to reach sampling site(s). A detailed location
map for the site which should shows the sample collection point with respect to prominent
landmarks in the area. In case there is any deviation in the collection point, record it on the
sample identification form giving reason.
3.4 Field measurements
For all water quality samples of open dynamic systems such as rivers, field measurements
must be made for : Temperature, pH, EC. and DO.
3.5 Labelling sample bottles and Completing Pro forma
Sample containers should be clearly and unambiguously marked. All details relevant to the
sample should be recorded and connected with the sample container.
54. 50
3.6 Preservation and Transport
Loss or transformation of the sample during sampling and transport needs to be controlled.
Common measures are conservation, cooled storage, cooled transport and minimizing the
time period between sampling and analysis (a maximum storage time before analysis can
even be specified).
• Samples should be transported to concerned laboratory (level II or II+) as soon as possible,
preferably within 48 hours.
• Analysis for coliforms should be started within 24 h of collection of sample. If time is
exceeded, it should be recorded with the result.
• Samples containing microgram/L metal level, should be stored at 4o
C and analysed as
soon as possible. If the concentration is of mg/L level, it can be stored for upto 6 months,
except mercury, for which the limit is 5 weeks.
• Discard samples only after primary validation of data.
3.7 Control Samples
• Field check samples to provide routine checks on sample stability. Checks can be done by
dividing a real sample in two and making a known addition to one portion. The recovery is
a check that conservation, sample transport and storage are satisfactory.
• Duplicate samples to provide checks on variability.
3.8 Sample control and documentation – Sample receipt register
• Each laboratory should have a bound register, which is used for registering
samples as they are received.
3.9 Work Assignment and Personal Registers
• The laboratory incharge should maintain a bound register for assignment of work.
This register would link the lab. sample number to the analyst who makes specific
analyses, such as pH, EC, BOD, etc.
• An estimate of time needed for performing the analyses may also be entered in
the register.
• Each laboratory analyst should have his/her own bound register, where all
laboratory readings and calculations are to be entered.
• When analysis and calculations are completed, the results must be recorded in a
register containing data record sheets described in the next section.
3.10 Maintenance of Equipment
Regular maintenance of laboratory equipment is key to making controlled analyses of water
samples.
55. 51
4. Recommendations
The primary goal of the Quality Assurance Programme in water quality monitoring is that the
information obtained from the monitoring system meets the required quality criteria. Those
using the data must have confidence in the data.
Important to Quality Assurance Programme is traceability. Traceability is concerned with
defining and documenting the processes and activities that lead to the information and how
the results are achieved. When the processes are known, activities can be conducted
correctly, and if not, measures can be taken to improve these processes.
Quality management requires a system where there are documented procedures for all the
relevant processes and products important in water quality monitoring and the responsibilities
with regard to the distinguished procedures.
Standards methods and techniques are defined for, among others, sampling, transport and
storage of samples, laboratory analysis, data validation, data storage and exchange,
calculation methods and statistical methods as part of the requirements. All these steps are
documented within the Hydrology Project. By following protocols, mistakes can mostly be
avoided, and any mistakes that are made may be traced and undone.
If monitoring data from different monitoring networks are to be compared, it is important that
the data be of comparable quality. Quality Assurance requires co-operation and participation
of all personnel involved with water quality monitoring activities. Quality assurance of Water
quality monitoring is the responsibility of the managers of the organisation and the device can
be achieved by good managerial practices.
Management has to ensure that the analysts have the knowledge as well as skill of
implementing analytical procedures. Any one can learn to turn knob and read galvanometers
or digital reading, but assurance that a measurement has been made in the best possible
system, must come from a Chemist.
56. 52
Analytical Quality Control programme
Dr. A. K. Mitra
1. Introduction
Analytical Quality Control (AQC) is one of the main components of a complete Quality
Assurance Programme for Water Quality Monitoring, wherein the quality of analytical data
being generated in any laboratory is controlled through minimising or controlling errors to
achieve a target accuracy. AQC is used to evaluate reliability of experiment data.
Why is it required?
Many studies have shown that analytical results are often subject to serious errors, particularly
at the low concentrations encountered in water analysis. In fact, the errors may be so large
that the validity of actions taken regarding management of water quality may become
questionable.
An analytical quality control exercise (AQC) conducted by United States Environmental
Protection Agency (US-EPA) showed a wide variation in results when identical samples were
analysed in 22 laboratories:
Nutrient Concentration,
mg/L
Range of results,
mg/L
Ammonia 0.26
1.71
0.09 - 0.39
1.44 - 2.46
Nitrate 0.19 0.08 - 0.41
Total phosphorus 0.882 0.642 - 1.407
It is seen that the range of values reported are significantly large, ±50% for ammonia and
±100% for nitrates, compared to the actual concentrations.
2. Types of AQC
Two types of AQC schemes are practised: Intra laboratory and Inter-laboratory AQC.
Intra-laboratory AQC :
Intra-laboratory AQC focuses on achieving precision or ‘reproducibility’ of analyses within one
laboratory. This can be achieved by following documented procedures for all analytical
activities. Important components to identify errors are control charts and control samples.
Inter-laboratory AQC:
The focus of inter-laboratory AQC is to achieve comparability of results in all the participating
laboratories by controlling the accuracy of each.
The main objectives of inter-laboratory AQC are:
(a)To test for possible bias in measurements in a laboratory.
(b)To provide direct evidence of comparability of results among laboratories in a common
water quality-monitoring programme such as Hydrology Project.
57. 53
3. Objectives of AQC
The objective of Analytical Quality Control is:
• To ensure meaningful water quality assessment
• To have confidence in results
• to assess the status of analytical facilities and capabilities of concerned laboratories.
• to identify the serious constraints (random & systematic) in the working environment of
laboratories.
• to provide necessary assistance to the concerned laboratories to overcome the short
comings in the analytical capabilities.
• to validate the water quality monitoring data.
• to promote scientific and analytical competence of the concerned laboratories to the level
of excellence for better output.
4. Basic statistics in AQC
True value – A value is accepted as being true when it is believed that uncertainty in the
value is less than the uncertainty in something else with which it is being compared.
Error – The term error refers to the numerical difference between a measured value and true
value.
Determinate errors or systematic errors – Determinate errors are generally unidirectional
with respect to true value, and in many cases they can be predicted. Examples are
incorrectly calibrated instrument, an impurity in a reagent or distilled water, a side reaction in a
titration and heating a sample at a temperature different from that required.
Bias is a measure of determinate errors.
Indeterminate errors – These types of errors cannot be attributed to any known cause.
They are random in nature and lead to both high and low results with equal probability. They
cannot be eliminated and are the ultimate limitation on the measurement.
Accuracy – An accurate result is one that agrees closely with the true value of a measured
quantity.
Precision – The term precision refers to the agreement among a group of experimental
results; it implies nothing about their relation to the true value.
Frequency distribution: Relation between the values of results of repetitive analyses of a
sample and the number of times (frequency) that a particular value occurs.
Mean: Mean is the central value of results of a set of repetitive analyses of a sample. It is
calculated by summing the individual observations and dividing it by the total number of
observations. Mean, ( x ), of a set of data is calculated by adding all the observed values of
variable (results of analyses) and dividing it by the total number of observations:
x x x x nx n= + +( ......... ) /1
where x1, x2,........xn are the observed values and n is the total number of observations.
58. 54
Standard deviation: Standard deviation is a measure of spread of results of repetitive
analyses of a sample around its mean value. It is a measure of precision of the analytical
method. It is calculated by taking square root of sum of squares of deviation of the
observations from the mean divided by the number of observations minus one. Standard
deviation, s, is calculated as:
)1/(}).......()(){( 22
2
2
1 −−+−+−= nxxxxxxs n x
A small value of s signifies that most of the observations are close to the mean value.
A large value indicates that the observed values are spread over a larger range.
Precision and standard deviation
The most important parameter to evaluate in the results is the precision. The statistical term to
evaluate precision is standard deviation. The numerical value of the standard deviation
depends on the average concentration (standard deviation also has the unit of concentration).
Normal distribution
Normal distribution is a frequency distribution, which is symmetrical around the mean. In a
normal distribution 95.5% and 99.7% of the observations lie in ± two times standard deviation
and ± three times standard deviation range around the mean, respectively.
Control Limits
Two sets of control limits are usually set: inner limits at about ± 2s (UWL & LWL) to warn of
possible trouble and outer limits of ± 3s (UCL & LCL) demanding a corrective. It has been
observed that 99.7% of a group of results should fall within the ± 3s limits unless a definite
cause is operating on the analysis. If the method is under control, approximately 4.5% of
results may be expected to fall outside the UWL & LWL lines. This type of chart provides a
check on both random and systematic error gauged from the spread of results
5. Components of an AQC Programme
5.1 Intra-Laboratory AQC
Types of Control Samples
Good Analytical Quality Control includes control samples such as :
• standard solutions
• recovery of known additions,
• analysis of reagent blanks, and
• analysis of duplicates
A control sample is a sample whose analytical results are used to check the procedures being
used and results being produced in the analytical laboratory. Different types of control
samples help to detect different types of error. Control samples should be representative of
the samples routinely analysed in terms of the determinant concentration. Examples of some
control samples and their characteristics and use are given below:
Standard Solution